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Author SHA1 Message Date
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ab916df19e Calling class methods statically implemented 2024-07-28 23:53:58 +08:00
75 changed files with 2156 additions and 7055 deletions

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@ -1,32 +0,0 @@
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1
.gitignore vendored
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@ -1,4 +1,3 @@
__pycache__
/target
/nac3standalone/demo/linalg/target
nix/windows/msys2

180
Cargo.lock generated
View File

@ -26,9 +26,9 @@ dependencies = [
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name = "anstream"
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version = "0.6.14"
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@ -41,36 +41,36 @@ dependencies = [
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name = "anstyle"
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dependencies = [
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@ -117,12 +117,9 @@ checksum = "1fd0f2584146f6f2ef48085050886acf353beff7305ebd1ae69500e27c67f64b"
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[[package]]
name = "cfg-if"
@ -132,9 +129,9 @@ checksum = "baf1de4339761588bc0619e3cbc0120ee582ebb74b53b4efbf79117bd2da40fd"
[[package]]
name = "clap"
version = "4.5.16"
version = "4.5.9"
source = "registry+https://github.com/rust-lang/crates.io-index"
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dependencies = [
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"clap_derive",
@ -142,9 +139,9 @@ dependencies = [
[[package]]
name = "clap_builder"
version = "4.5.15"
version = "4.5.9"
source = "registry+https://github.com/rust-lang/crates.io-index"
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dependencies = [
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@ -154,27 +151,27 @@ dependencies = [
[[package]]
name = "clap_derive"
version = "4.5.13"
version = "4.5.8"
source = "registry+https://github.com/rust-lang/crates.io-index"
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dependencies = [
"heck 0.5.0",
"proc-macro2",
"quote",
"syn 2.0.76",
"syn 2.0.71",
]
[[package]]
name = "clap_lex"
version = "0.7.2"
version = "0.7.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
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name = "colorchoice"
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[[package]]
name = "console"
@ -185,7 +182,7 @@ dependencies = [
"encode_unicode",
"lazy_static",
"libc",
"windows-sys 0.52.0",
"windows-sys",
]
[[package]]
@ -305,14 +302,14 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "534c5cf6194dfab3db3242765c03bbe257cf92f22b38f6bc0c58d59108a820ba"
dependencies = [
"libc",
"windows-sys 0.52.0",
"windows-sys",
]
[[package]]
name = "fastrand"
version = "2.1.1"
version = "2.1.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
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@ -388,9 +385,9 @@ dependencies = [
[[package]]
name = "indexmap"
version = "2.4.0"
version = "2.2.6"
source = "registry+https://github.com/rust-lang/crates.io-index"
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@ -424,7 +421,7 @@ checksum = "4fa4d8d74483041a882adaa9a29f633253a66dde85055f0495c121620ac484b2"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.76",
"syn 2.0.71",
]
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@ -443,9 +440,9 @@ dependencies = [
[[package]]
name = "is_terminal_polyfill"
version = "1.70.1"
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@ -510,9 +507,9 @@ checksum = "bbd2bcb4c963f2ddae06a2efc7e9f3591312473c50c6685e1f298068316e66fe"
[[package]]
name = "libc"
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checksum = "97b3888a4aecf77e811145cadf6eef5901f4782c53886191b2f693f24761847c"
[[package]]
name = "libloading"
@ -619,7 +616,7 @@ name = "nac3core"
version = "0.1.0"
dependencies = [
"crossbeam",
"indexmap 2.4.0",
"indexmap 2.2.6",
"indoc",
"inkwell",
"insta",
@ -709,7 +706,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "b4c5cc86750666a3ed20bdaf5ca2a0344f9c67674cae0515bec2da16fbaa47db"
dependencies = [
"fixedbitset",
"indexmap 2.4.0",
"indexmap 2.2.6",
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[[package]]
@ -752,7 +749,7 @@ dependencies = [
"phf_shared 0.11.2",
"proc-macro2",
"quote",
"syn 2.0.76",
"syn 2.0.71",
]
[[package]]
@ -787,12 +784,9 @@ checksum = "da544ee218f0d287a911e9c99a39a8c9bc8fcad3cb8db5959940044ecfc67265"
[[package]]
name = "ppv-lite86"
version = "0.2.20"
version = "0.2.17"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "77957b295656769bb8ad2b6a6b09d897d94f05c41b069aede1fcdaa675eaea04"
dependencies = [
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]
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[[package]]
name = "precomputed-hash"
@ -856,7 +850,7 @@ dependencies = [
"proc-macro2",
"pyo3-macros-backend",
"quote",
"syn 2.0.76",
"syn 2.0.71",
]
[[package]]
@ -869,14 +863,14 @@ dependencies = [
"proc-macro2",
"pyo3-build-config",
"quote",
"syn 2.0.76",
"syn 2.0.71",
]
[[package]]
name = "quote"
version = "1.0.37"
version = "1.0.36"
source = "registry+https://github.com/rust-lang/crates.io-index"
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dependencies = [
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@ -942,9 +936,9 @@ dependencies = [
[[package]]
name = "redox_users"
version = "0.4.6"
version = "0.4.5"
source = "registry+https://github.com/rust-lang/crates.io-index"
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dependencies = [
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@ -953,9 +947,9 @@ dependencies = [
[[package]]
name = "regex"
version = "1.10.6"
version = "1.10.5"
source = "registry+https://github.com/rust-lang/crates.io-index"
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dependencies = [
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"memchr",
@ -989,15 +983,15 @@ dependencies = [
[[package]]
name = "rustix"
version = "0.38.35"
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source = "registry+https://github.com/rust-lang/crates.io-index"
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"bitflags",
"errno",
"libc",
"linux-raw-sys",
"windows-sys 0.52.0",
"windows-sys",
]
[[package]]
@ -1035,32 +1029,31 @@ checksum = "61697e0a1c7e512e84a621326239844a24d8207b4669b41bc18b32ea5cbf988b"
[[package]]
name = "serde"
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checksum = "bc76f558e0cbb2a839d37354c575f1dc3fdc6546b5be373ba43d95f231bf7c12"
dependencies = [
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]
[[package]]
name = "serde_derive"
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version = "1.0.204"
source = "registry+https://github.com/rust-lang/crates.io-index"
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dependencies = [
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"quote",
"syn 2.0.76",
"syn 2.0.71",
]
[[package]]
name = "serde_json"
version = "1.0.127"
version = "1.0.120"
source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "4e0d21c9a8cae1235ad58a00c11cb40d4b1e5c784f1ef2c537876ed6ffd8b7c5"
dependencies = [
"itoa",
"memchr",
"ryu",
"serde",
]
@ -1077,17 +1070,11 @@ dependencies = [
"yaml-rust",
]
[[package]]
name = "shlex"
version = "1.3.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "0fda2ff0d084019ba4d7c6f371c95d8fd75ce3524c3cb8fb653a3023f6323e64"
[[package]]
name = "similar"
version = "2.6.0"
version = "2.5.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "1de1d4f81173b03af4c0cbed3c898f6bff5b870e4a7f5d6f4057d62a7a4b686e"
checksum = "fa42c91313f1d05da9b26f267f931cf178d4aba455b4c4622dd7355eb80c6640"
[[package]]
name = "siphasher"
@ -1147,7 +1134,7 @@ dependencies = [
"proc-macro2",
"quote",
"rustversion",
"syn 2.0.76",
"syn 2.0.71",
]
[[package]]
@ -1163,9 +1150,9 @@ dependencies = [
[[package]]
name = "syn"
version = "2.0.76"
version = "2.0.71"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "578e081a14e0cefc3279b0472138c513f37b41a08d5a3cca9b6e4e8ceb6cd525"
checksum = "b146dcf730474b4bcd16c311627b31ede9ab149045db4d6088b3becaea046462"
dependencies = [
"proc-macro2",
"quote",
@ -1174,21 +1161,20 @@ dependencies = [
[[package]]
name = "target-lexicon"
version = "0.12.16"
version = "0.12.15"
source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "4873307b7c257eddcb50c9bedf158eb669578359fb28428bef438fec8e6ba7c2"
[[package]]
name = "tempfile"
version = "3.12.0"
version = "3.10.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
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checksum = "85b77fafb263dd9d05cbeac119526425676db3784113aa9295c88498cbf8bff1"
dependencies = [
"cfg-if",
"fastrand",
"once_cell",
"rustix",
"windows-sys 0.59.0",
"windows-sys",
]
[[package]]
@ -1232,7 +1218,7 @@ checksum = "a4558b58466b9ad7ca0f102865eccc95938dca1a74a856f2b57b6629050da261"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.76",
"syn 2.0.71",
]
[[package]]
@ -1310,9 +1296,9 @@ checksum = "0336d538f7abc86d282a4189614dfaa90810dfc2c6f6427eaf88e16311dd225d"
[[package]]
name = "unicode-xid"
version = "0.2.5"
version = "0.2.4"
source = "registry+https://github.com/rust-lang/crates.io-index"
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[[package]]
name = "unicode_names2"
@ -1350,9 +1336,9 @@ checksum = "06abde3611657adf66d383f00b093d7faecc7fa57071cce2578660c9f1010821"
[[package]]
name = "version_check"
version = "0.9.5"
version = "0.9.4"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "0b928f33d975fc6ad9f86c8f283853ad26bdd5b10b7f1542aa2fa15e2289105a"
checksum = "49874b5167b65d7193b8aba1567f5c7d93d001cafc34600cee003eda787e483f"
[[package]]
name = "walkdir"
@ -1388,11 +1374,11 @@ checksum = "ac3b87c63620426dd9b991e5ce0329eff545bccbbb34f3be09ff6fb6ab51b7b6"
[[package]]
name = "winapi-util"
version = "0.1.9"
version = "0.1.8"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "cf221c93e13a30d793f7645a0e7762c55d169dbb0a49671918a2319d289b10bb"
checksum = "4d4cc384e1e73b93bafa6fb4f1df8c41695c8a91cf9c4c64358067d15a7b6c6b"
dependencies = [
"windows-sys 0.59.0",
"windows-sys",
]
[[package]]
@ -1410,15 +1396,6 @@ dependencies = [
"windows-targets",
]
[[package]]
name = "windows-sys"
version = "0.59.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "1e38bc4d79ed67fd075bcc251a1c39b32a1776bbe92e5bef1f0bf1f8c531853b"
dependencies = [
"windows-targets",
]
[[package]]
name = "windows-targets"
version = "0.52.6"
@ -1498,7 +1475,6 @@ version = "0.7.35"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "1b9b4fd18abc82b8136838da5d50bae7bdea537c574d8dc1a34ed098d6c166f0"
dependencies = [
"byteorder",
"zerocopy-derive",
]
@ -1510,5 +1486,5 @@ checksum = "fa4f8080344d4671fb4e831a13ad1e68092748387dfc4f55e356242fae12ce3e"
dependencies = [
"proc-macro2",
"quote",
"syn 2.0.76",
"syn 2.0.71",
]

6
flake.lock generated
View File

@ -2,11 +2,11 @@
"nodes": {
"nixpkgs": {
"locked": {
"lastModified": 1724819573,
"narHash": "sha256-GnR7/ibgIH1vhoy8cYdmXE6iyZqKqFxQSVkFgosBh6w=",
"lastModified": 1720418205,
"narHash": "sha256-cPJoFPXU44GlhWg4pUk9oUPqurPlCFZ11ZQPk21GTPU=",
"owner": "NixOS",
"repo": "nixpkgs",
"rev": "71e91c409d1e654808b2621f28a327acfdad8dc2",
"rev": "655a58a72a6601292512670343087c2d75d859c1",
"type": "github"
},
"original": {

View File

@ -6,7 +6,6 @@
outputs = { self, nixpkgs }:
let
pkgs = import nixpkgs { system = "x86_64-linux"; };
pkgs32 = import nixpkgs { system = "i686-linux"; };
in rec {
packages.x86_64-linux = rec {
llvm-nac3 = pkgs.callPackage ./nix/llvm {};
@ -16,22 +15,6 @@
ln -s ${pkgs.llvmPackages_14.clang-unwrapped}/bin/clang $out/bin/clang-irrt
ln -s ${pkgs.llvmPackages_14.llvm.out}/bin/llvm-as $out/bin/llvm-as-irrt
'';
demo-linalg-stub = pkgs.rustPlatform.buildRustPackage {
name = "demo-linalg-stub";
src = ./nac3standalone/demo/linalg;
cargoLock = {
lockFile = ./nac3standalone/demo/linalg/Cargo.lock;
};
doCheck = false;
};
demo-linalg-stub32 = pkgs32.rustPlatform.buildRustPackage {
name = "demo-linalg-stub32";
src = ./nac3standalone/demo/linalg;
cargoLock = {
lockFile = ./nac3standalone/demo/linalg/Cargo.lock;
};
doCheck = false;
};
nac3artiq = pkgs.python3Packages.toPythonModule (
pkgs.rustPlatform.buildRustPackage rec {
name = "nac3artiq";
@ -41,7 +24,7 @@
lockFile = ./Cargo.lock;
};
passthru.cargoLock = cargoLock;
nativeBuildInputs = [ pkgs.python3 (pkgs.wrapClangMulti pkgs.llvmPackages_14.clang) llvm-tools-irrt pkgs.llvmPackages_14.llvm.out llvm-nac3 ];
nativeBuildInputs = [ pkgs.python3 pkgs.llvmPackages_14.clang llvm-tools-irrt pkgs.llvmPackages_14.llvm.out llvm-nac3 ];
buildInputs = [ pkgs.python3 llvm-nac3 ];
checkInputs = [ (pkgs.python3.withPackages(ps: [ ps.numpy ps.scipy ])) ];
checkPhase =
@ -49,9 +32,7 @@
echo "Checking nac3standalone demos..."
pushd nac3standalone/demo
patchShebangs .
export DEMO_LINALG_STUB=${demo-linalg-stub}/lib/liblinalg.a
export DEMO_LINALG_STUB32=${demo-linalg-stub32}/lib/liblinalg.a
./check_demos.sh -i686
./check_demos.sh
popd
echo "Running Cargo tests..."
cargoCheckHook
@ -168,7 +149,7 @@
buildInputs = with pkgs; [
# build dependencies
packages.x86_64-linux.llvm-nac3
(pkgs.wrapClangMulti llvmPackages_14.clang) llvmPackages_14.llvm.out # for running nac3standalone demos
llvmPackages_14.clang llvmPackages_14.llvm.out # for running nac3standalone demos
packages.x86_64-linux.llvm-tools-irrt
cargo
rustc
@ -180,12 +161,9 @@
clippy
pre-commit
rustfmt
rust-analyzer
];
shellHook =
''
export DEMO_LINALG_STUB=${packages.x86_64-linux.demo-linalg-stub}/lib/liblinalg.a
export DEMO_LINALG_STUB32=${packages.x86_64-linux.demo-linalg-stub32}/lib/liblinalg.a
'';
RUST_SRC_PATH = "${pkgs.rust.packages.stable.rustPlatform.rustLibSrc}";
};
devShells.x86_64-linux.msys2 = pkgs.mkShell {
name = "nac3-dev-shell-msys2";

View File

@ -24,4 +24,3 @@ features = ["llvm14-0", "target-x86", "target-arm", "target-riscv", "no-libffi-l
[features]
init-llvm-profile = []
no-escape-analysis = ["nac3core/no-escape-analysis"]

View File

@ -1,26 +0,0 @@
from min_artiq import *
from numpy import ndarray, zeros as np_zeros
@nac3
class StrFail:
core: KernelInvariant[Core]
def __init__(self):
self.core = Core()
@kernel
def hello(self, arg: str):
pass
@kernel
def consume_ndarray(self, arg: ndarray[str, 1]):
pass
def run(self):
self.hello("world")
self.consume_ndarray(np_zeros([10], dtype=str))
if __name__ == "__main__":
StrFail().run()

File diff suppressed because it is too large Load Diff

View File

@ -24,7 +24,6 @@ use std::rc::Rc;
use std::sync::Arc;
use inkwell::{
context::Context,
memory_buffer::MemoryBuffer,
module::{Linkage, Module},
passes::PassBuilderOptions,
@ -35,7 +34,7 @@ use inkwell::{
use itertools::Itertools;
use nac3core::codegen::{gen_func_impl, CodeGenLLVMOptions, CodeGenTargetMachineOptions};
use nac3core::toplevel::builtins::get_exn_constructor;
use nac3core::typecheck::typedef::{into_var_map, TypeEnum, Unifier, VarMap};
use nac3core::typecheck::typedef::{TypeEnum, Unifier, VarMap};
use nac3parser::{
ast::{ExprKind, Stmt, StmtKind, StrRef},
parser::parse_program,
@ -51,7 +50,7 @@ use nac3core::{
codegen::{concrete_type::ConcreteTypeStore, CodeGenTask, WithCall, WorkerRegistry},
symbol_resolver::SymbolResolver,
toplevel::{
composer::{BuiltinFuncCreator, BuiltinFuncSpec, ComposerConfig, TopLevelComposer},
composer::{ComposerConfig, TopLevelComposer},
DefinitionId, GenCall, TopLevelDef,
},
typecheck::typedef::{FunSignature, FuncArg},
@ -60,13 +59,13 @@ use nac3core::{
use nac3ld::Linker;
use tempfile::{self, TempDir};
use crate::codegen::attributes_writeback;
use crate::{
codegen::{
attributes_writeback, gen_core_log, gen_rtio_log, rpc_codegen_callback, ArtiqCodeGenerator,
},
codegen::{rpc_codegen_callback, ArtiqCodeGenerator},
symbol_resolver::{DeferredEvaluationStore, InnerResolver, PythonHelper, Resolver},
};
use tempfile::{self, TempDir};
mod codegen;
mod symbol_resolver;
@ -127,7 +126,7 @@ struct Nac3 {
isa: Isa,
time_fns: &'static (dyn TimeFns + Sync),
primitive: PrimitiveStore,
builtins: Vec<BuiltinFuncSpec>,
builtins: Vec<(StrRef, FunSignature, Arc<GenCall>)>,
pyid_to_def: Arc<RwLock<HashMap<u64, DefinitionId>>>,
primitive_ids: PrimitivePythonId,
working_directory: TempDir,
@ -265,7 +264,7 @@ impl Nac3 {
arg_names.len(),
));
}
for (i, FuncArg { ty, default_value, name, .. }) in args.iter().enumerate() {
for (i, FuncArg { ty, default_value, name }) in args.iter().enumerate() {
let in_name = match arg_names.get(i) {
Some(n) => n,
None if default_value.is_none() => {
@ -301,64 +300,6 @@ impl Nac3 {
None
}
/// Returns a [`Vec`] of builtins that needs to be initialized during method compilation time.
fn get_lateinit_builtins() -> Vec<Box<BuiltinFuncCreator>> {
vec![
Box::new(|primitives, unifier| {
let arg_ty = unifier.get_fresh_var(Some("T".into()), None);
(
"core_log".into(),
FunSignature {
args: vec![FuncArg {
name: "arg".into(),
ty: arg_ty.ty,
default_value: None,
is_vararg: false,
}],
ret: primitives.none,
vars: into_var_map([arg_ty]),
},
Arc::new(GenCall::new(Box::new(move |ctx, obj, fun, args, generator| {
gen_core_log(ctx, &obj, fun, &args, generator)?;
Ok(None)
}))),
)
}),
Box::new(|primitives, unifier| {
let arg_ty = unifier.get_fresh_var(Some("T".into()), None);
(
"rtio_log".into(),
FunSignature {
args: vec![
FuncArg {
name: "channel".into(),
ty: primitives.str,
default_value: None,
is_vararg: false,
},
FuncArg {
name: "arg".into(),
ty: arg_ty.ty,
default_value: None,
is_vararg: false,
},
],
ret: primitives.none,
vars: into_var_map([arg_ty]),
},
Arc::new(GenCall::new(Box::new(move |ctx, obj, fun, args, generator| {
gen_rtio_log(ctx, &obj, fun, &args, generator)?;
Ok(None)
}))),
)
}),
]
}
fn compile_method<T>(
&self,
obj: &PyAny,
@ -371,7 +312,6 @@ impl Nac3 {
let size_t = self.isa.get_size_type();
let (mut composer, mut builtins_def, mut builtins_ty) = TopLevelComposer::new(
self.builtins.clone(),
Self::get_lateinit_builtins(),
ComposerConfig { kernel_ann: Some("Kernel"), kernel_invariant_ann: "KernelInvariant" },
size_t,
);
@ -448,6 +388,7 @@ impl Nac3 {
pyid_to_type: pyid_to_type.clone(),
primitive_ids: self.primitive_ids.clone(),
global_value_ids: global_value_ids.clone(),
class_names: Mutex::default(),
name_to_pyid: name_to_pyid.clone(),
module: module.clone(),
id_to_pyval: RwLock::default(),
@ -539,6 +480,7 @@ impl Nac3 {
pyid_to_type: pyid_to_type.clone(),
primitive_ids: self.primitive_ids.clone(),
global_value_ids: global_value_ids.clone(),
class_names: Mutex::default(),
id_to_pyval: RwLock::default(),
id_to_primitive: RwLock::default(),
field_to_val: RwLock::default(),
@ -555,10 +497,6 @@ impl Nac3 {
.register_top_level(synthesized.pop().unwrap(), Some(resolver.clone()), "", false)
.unwrap();
// Process IRRT
let context = inkwell::context::Context::create();
let irrt = load_irrt(&context, resolver.as_ref());
let fun_signature =
FunSignature { args: vec![], ret: self.primitive.none, vars: VarMap::new() };
let mut store = ConcreteTypeStore::new();
@ -687,9 +625,7 @@ impl Nac3 {
let buffer = buffer.as_slice().into();
membuffer.lock().push(buffer);
})));
let size_t = Context::create()
.ptr_sized_int_type(&self.get_llvm_target_machine().get_target_data(), None)
.get_bit_width();
let size_t = if self.isa == Isa::Host { 64 } else { 32 };
let num_threads = if is_multithreaded() { 4 } else { 1 };
let thread_names: Vec<String> = (0..num_threads).map(|_| "main".to_string()).collect();
let threads: Vec<_> = thread_names
@ -708,9 +644,6 @@ impl Nac3 {
ArtiqCodeGenerator::new("attributes_writeback".to_string(), size_t, self.time_fns);
let context = inkwell::context::Context::create();
let module = context.create_module("attributes_writeback");
let target_machine = self.llvm_options.create_target_machine().unwrap();
module.set_data_layout(&target_machine.get_target_data().get_data_layout());
module.set_triple(&target_machine.get_triple());
let builder = context.create_builder();
let (_, module, _) = gen_func_impl(
&context,
@ -729,7 +662,7 @@ impl Nac3 {
membuffer.lock().push(buffer);
});
// Link all modules into `main`.
let context = inkwell::context::Context::create();
let buffers = membuffers.lock();
let main = context
.create_module_from_ir(MemoryBuffer::create_from_memory_range(&buffers[0], "main"))
@ -758,7 +691,8 @@ impl Nac3 {
)
.unwrap();
main.link_in_module(irrt).map_err(|err| CompileError::new_err(err.to_string()))?;
main.link_in_module(load_irrt(&context))
.map_err(|err| CompileError::new_err(err.to_string()))?;
let mut function_iter = main.get_first_function();
while let Some(func) = function_iter {
@ -913,7 +847,7 @@ impl Nac3 {
Isa::RiscV32IMA => &timeline::NOW_PINNING_TIME_FNS,
Isa::CortexA9 | Isa::Host => &timeline::EXTERN_TIME_FNS,
};
let (primitive, _) = TopLevelComposer::make_primitives(isa.get_size_type());
let primitive: PrimitiveStore = TopLevelComposer::make_primitives(isa.get_size_type()).0;
let builtins = vec![
(
"now_mu".into(),
@ -929,7 +863,6 @@ impl Nac3 {
name: "t".into(),
ty: primitive.int64,
default_value: None,
is_vararg: false,
}],
ret: primitive.none,
vars: VarMap::new(),
@ -949,7 +882,6 @@ impl Nac3 {
name: "dt".into(),
ty: primitive.int64,
default_value: None,
is_vararg: false,
}],
ret: primitive.none,
vars: VarMap::new(),

View File

@ -1,6 +1,4 @@
use crate::PrimitivePythonId;
use inkwell::{
module::Linkage,
types::{BasicType, BasicTypeEnum},
values::BasicValueEnum,
AddressSpace,
@ -23,7 +21,7 @@ use nac3core::{
},
};
use nac3parser::ast::{self, StrRef};
use parking_lot::RwLock;
use parking_lot::{Mutex, RwLock};
use pyo3::{
types::{PyDict, PyTuple},
PyAny, PyObject, PyResult, Python,
@ -36,6 +34,8 @@ use std::{
},
};
use crate::PrimitivePythonId;
pub enum PrimitiveValue {
I32(i32),
I64(i64),
@ -79,6 +79,7 @@ pub struct InnerResolver {
pub id_to_primitive: RwLock<HashMap<u64, PrimitiveValue>>,
pub field_to_val: RwLock<HashMap<ResolverField, Option<PyFieldHandle>>>,
pub global_value_ids: Arc<RwLock<HashMap<u64, PyObject>>>,
pub class_names: Mutex<HashMap<StrRef, Type>>,
pub pyid_to_def: Arc<RwLock<HashMap<u64, DefinitionId>>>,
pub pyid_to_type: Arc<RwLock<HashMap<u64, Type>>>,
pub primitive_ids: PrimitivePythonId,
@ -132,8 +133,6 @@ impl StaticValue for PythonValue {
format!("{}_const", self.id).as_str(),
);
global.set_constant(true);
// Set linkage of global to private to avoid name collisions
global.set_linkage(Linkage::Private);
global.set_initializer(&ctx.ctx.const_struct(
&[ctx.ctx.i32_type().const_int(u64::from(id), false).into()],
false,
@ -164,7 +163,7 @@ impl StaticValue for PythonValue {
PrimitiveValue::Bool(val) => {
ctx.ctx.i8_type().const_int(u64::from(*val), false).into()
}
PrimitiveValue::Str(val) => ctx.gen_string(generator, val).into(),
PrimitiveValue::Str(val) => ctx.ctx.const_string(val.as_bytes(), true).into(),
});
}
if let Some(global) = ctx.module.get_global(&self.id.to_string()) {
@ -352,7 +351,7 @@ impl InnerResolver {
Ok(Ok((ndarray, false)))
} else if ty_id == self.primitive_ids.tuple {
// do not handle type var param and concrete check here
Ok(Ok((unifier.add_ty(TypeEnum::TTuple { ty: vec![], is_vararg_ctx: false }), false)))
Ok(Ok((unifier.add_ty(TypeEnum::TTuple { ty: vec![] }), false)))
} else if ty_id == self.primitive_ids.option {
Ok(Ok((primitives.option, false)))
} else if ty_id == self.primitive_ids.none {
@ -556,10 +555,7 @@ impl InnerResolver {
Err(err) => return Ok(Err(err)),
_ => return Ok(Err("tuple type needs at least 1 type parameters".to_string()))
};
Ok(Ok((
unifier.add_ty(TypeEnum::TTuple { ty: args, is_vararg_ctx: false }),
true,
)))
Ok(Ok((unifier.add_ty(TypeEnum::TTuple { ty: args }), true)))
}
TypeEnum::TObj { params, obj_id, .. } => {
let subst = {
@ -801,9 +797,7 @@ impl InnerResolver {
.map(|elem| self.get_obj_type(py, elem, unifier, defs, primitives))
.collect();
let types = types?;
Ok(types.map(|types| {
unifier.add_ty(TypeEnum::TTuple { ty: types, is_vararg_ctx: false })
}))
Ok(types.map(|types| unifier.add_ty(TypeEnum::TTuple { ty: types })))
}
// special handling for option type since its class member layout in python side
// is special and cannot be mapped directly to a nac3 type as below
@ -978,7 +972,7 @@ impl InnerResolver {
} else if ty_id == self.primitive_ids.string || ty_id == self.primitive_ids.np_str_ {
let val: String = obj.extract().unwrap();
self.id_to_primitive.write().insert(id, PrimitiveValue::Str(val.clone()));
Ok(Some(ctx.gen_string(generator, val).into()))
Ok(Some(ctx.ctx.const_string(val.as_bytes(), true).into()))
} else if ty_id == self.primitive_ids.float || ty_id == self.primitive_ids.float64 {
let val: f64 = obj.extract().unwrap();
self.id_to_primitive.write().insert(id, PrimitiveValue::F64(val));
@ -1209,9 +1203,7 @@ impl InnerResolver {
Ok(Some(ndarray.as_pointer_value().into()))
} else if ty_id == self.primitive_ids.tuple {
let expected_ty_enum = ctx.unifier.get_ty_immutable(expected_ty);
let TypeEnum::TTuple { ty, is_vararg_ctx: false } = expected_ty_enum.as_ref() else {
unreachable!()
};
let TypeEnum::TTuple { ty } = expected_ty_enum.as_ref() else { unreachable!() };
let tup_tys = ty.iter();
let elements: &PyTuple = obj.downcast()?;
@ -1468,6 +1460,7 @@ impl SymbolResolver for Resolver {
id: StrRef,
_: &mut CodeGenContext<'ctx, '_>,
) -> Option<ValueEnum<'ctx>> {
println!("dc");
let sym_value = {
let id_to_val = self.0.id_to_pyval.read();
id_to_val.get(&id).cloned()

View File

@ -4,9 +4,6 @@ version = "0.1.0"
authors = ["M-Labs"]
edition = "2021"
[features]
no-escape-analysis = []
[dependencies]
itertools = "0.13"
crossbeam = "0.8"
@ -14,8 +11,8 @@ indexmap = "2.2"
parking_lot = "0.12"
rayon = "1.8"
nac3parser = { path = "../nac3parser" }
strum = "0.26"
strum_macros = "0.26"
strum = "0.26.2"
strum_macros = "0.26.4"
[dependencies.inkwell]
version = "0.4"

View File

@ -8,50 +8,37 @@ use std::{
};
fn main() {
let out_dir = env::var("OUT_DIR").unwrap();
let out_dir = Path::new(&out_dir);
let irrt_dir = Path::new("irrt");
let irrt_cpp_path = irrt_dir.join("irrt.cpp");
const FILE: &str = "src/codegen/irrt/irrt.cpp";
/*
* HACK: Sadly, clang doesn't let us emit generic LLVM bitcode.
* Compiling for WASM32 and filtering the output with regex is the closest we can get.
*/
let mut flags: Vec<&str> = vec![
let flags: &[&str] = &[
"--target=wasm32",
FILE,
"-x",
"c++",
"-std=c++20",
"-fno-discard-value-names",
"-fno-exceptions",
"-fno-rtti",
match env::var("PROFILE").as_deref() {
Ok("debug") => "-O0",
Ok("release") => "-O3",
flavor => panic!("Unknown or missing build flavor {flavor:?}"),
},
"-emit-llvm",
"-S",
"-Wall",
"-Wextra",
"-o",
"-",
"-I",
irrt_dir.to_str().unwrap(),
irrt_cpp_path.to_str().unwrap(),
];
match env::var("PROFILE").as_deref() {
Ok("debug") => {
flags.push("-O0");
flags.push("-DIRRT_DEBUG_ASSERT");
}
Ok("release") => {
flags.push("-O3");
}
flavor => panic!("Unknown or missing build flavor {flavor:?}"),
}
println!("cargo:rerun-if-changed={FILE}");
let out_dir = env::var("OUT_DIR").unwrap();
let out_path = Path::new(&out_dir);
// Tell Cargo to rerun if any file under `irrt_dir` (recursive) changes
println!("cargo:rerun-if-changed={}", irrt_dir.to_str().unwrap());
// Compile IRRT and capture the LLVM IR output
let output = Command::new("clang-irrt")
.args(flags)
.output()
@ -65,17 +52,7 @@ fn main() {
let output = std::str::from_utf8(&output.stdout).unwrap().replace("\r\n", "\n");
let mut filtered_output = String::with_capacity(output.len());
// Filter out irrelevant IR
//
// Regex:
// - `(?ms:^define.*?\}$)` captures LLVM `define` blocks
// - `(?m:^declare.*?$)` captures LLVM `declare` lines
// - `(?m:^%.+?=\s*type\s*\{.+?\}$)` captures LLVM `type` declarations
// - `(?m:^@.+?=.+$)` captures global constants
let regex_filter = Regex::new(
r"(?ms:^define.*?\}$)|(?m:^declare.*?$)|(?m:^%.+?=\s*type\s*\{.+?\}$)|(?m:^@.+?=.+$)",
)
.unwrap();
let regex_filter = Regex::new(r"(?ms:^define.*?\}$)|(?m:^declare.*?$)").unwrap();
for f in regex_filter.captures_iter(&output) {
assert_eq!(f.len(), 1);
filtered_output.push_str(&f[0]);
@ -86,22 +63,18 @@ fn main() {
.unwrap()
.replace_all(&filtered_output, "");
// For debugging
// Doing `DEBUG_DUMP_IRRT=1 cargo build -p nac3core` dumps the LLVM IR generated
const DEBUG_DUMP_IRRT: &str = "DEBUG_DUMP_IRRT";
println!("cargo:rerun-if-env-changed={DEBUG_DUMP_IRRT}");
if env::var(DEBUG_DUMP_IRRT).is_ok() {
let mut file = File::create(out_dir.join("irrt.ll")).unwrap();
println!("cargo:rerun-if-env-changed=DEBUG_DUMP_IRRT");
if env::var("DEBUG_DUMP_IRRT").is_ok() {
let mut file = File::create(out_path.join("irrt.ll")).unwrap();
file.write_all(output.as_bytes()).unwrap();
let mut file = File::create(out_dir.join("irrt-filtered.ll")).unwrap();
let mut file = File::create(out_path.join("irrt-filtered.ll")).unwrap();
file.write_all(filtered_output.as_bytes()).unwrap();
}
let mut llvm_as = Command::new("llvm-as-irrt")
.stdin(Stdio::piped())
.arg("-o")
.arg(out_dir.join("irrt.bc"))
.arg(out_path.join("irrt.bc"))
.spawn()
.unwrap();
llvm_as.stdin.as_mut().unwrap().write_all(filtered_output.as_bytes()).unwrap();

View File

@ -1,6 +0,0 @@
#include "irrt/exception.hpp"
#include "irrt/int_types.hpp"
#include "irrt/list.hpp"
#include "irrt/math.hpp"
#include "irrt/ndarray.hpp"
#include "irrt/slice.hpp"

View File

@ -1,9 +0,0 @@
#pragma once
#include "irrt/int_types.hpp"
template<typename SizeT>
struct CSlice {
uint8_t* base;
SizeT len;
};

View File

@ -1,25 +0,0 @@
#pragma once
// Set in nac3core/build.rs
#ifdef IRRT_DEBUG_ASSERT
#define IRRT_DEBUG_ASSERT_BOOL true
#else
#define IRRT_DEBUG_ASSERT_BOOL false
#endif
#define raise_debug_assert(SizeT, msg, param1, param2, param3) \
raise_exception(SizeT, EXN_ASSERTION_ERROR, "IRRT debug assert failed: " msg, param1, param2, param3)
#define debug_assert_eq(SizeT, lhs, rhs) \
if constexpr (IRRT_DEBUG_ASSERT_BOOL) { \
if ((lhs) != (rhs)) { \
raise_debug_assert(SizeT, "LHS = {0}. RHS = {1}", lhs, rhs, NO_PARAM); \
} \
}
#define debug_assert(SizeT, expr) \
if constexpr (IRRT_DEBUG_ASSERT_BOOL) { \
if (!(expr)) { \
raise_debug_assert(SizeT, "Got false.", NO_PARAM, NO_PARAM, NO_PARAM); \
} \
}

View File

@ -1,82 +0,0 @@
#pragma once
#include "irrt/cslice.hpp"
#include "irrt/int_types.hpp"
/**
* @brief The int type of ARTIQ exception IDs.
*/
typedef int32_t ExceptionId;
/*
* Set of exceptions C++ IRRT can use.
* Must be synchronized with `setup_irrt_exceptions` in `nac3core/src/codegen/irrt/mod.rs`.
*/
extern "C" {
ExceptionId EXN_INDEX_ERROR;
ExceptionId EXN_VALUE_ERROR;
ExceptionId EXN_ASSERTION_ERROR;
ExceptionId EXN_TYPE_ERROR;
}
/**
* @brief Extern function to `__nac3_raise`
*
* The parameter `err` could be `Exception<int32_t>` or `Exception<int64_t>`. The caller
* must make sure to pass `Exception`s with the correct `SizeT` depending on the `size_t` of the runtime.
*/
extern "C" void __nac3_raise(void* err);
namespace {
/**
* @brief NAC3's Exception struct
*/
template<typename SizeT>
struct Exception {
ExceptionId id;
CSlice<SizeT> filename;
int32_t line;
int32_t column;
CSlice<SizeT> function;
CSlice<SizeT> msg;
int64_t params[3];
};
constexpr int64_t NO_PARAM = 0;
template<typename SizeT>
void _raise_exception_helper(ExceptionId id,
const char* filename,
int32_t line,
const char* function,
const char* msg,
int64_t param0,
int64_t param1,
int64_t param2) {
Exception<SizeT> e = {
.id = id,
.filename = {.base = reinterpret_cast<const uint8_t*>(filename), .len = __builtin_strlen(filename)},
.line = line,
.column = 0,
.function = {.base = reinterpret_cast<const uint8_t*>(function), .len = __builtin_strlen(function)},
.msg = {.base = reinterpret_cast<const uint8_t*>(msg), .len = __builtin_strlen(msg)},
};
e.params[0] = param0;
e.params[1] = param1;
e.params[2] = param2;
__nac3_raise(reinterpret_cast<void*>(&e));
__builtin_unreachable();
}
/**
* @brief Raise an exception with location details (location in the IRRT source files).
* @param SizeT The runtime `size_t` type.
* @param id The ID of the exception to raise.
* @param msg A global constant C-string of the error message.
*
* `param0` to `param2` are optional format arguments of `msg`. They should be set to
* `NO_PARAM` to indicate they are unused.
*/
#define raise_exception(SizeT, id, msg, param0, param1, param2) \
_raise_exception_helper<SizeT>(id, __FILE__, __LINE__, __FUNCTION__, msg, param0, param1, param2)
} // namespace

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@ -1,13 +0,0 @@
#pragma once
using int8_t = _BitInt(8);
using uint8_t = unsigned _BitInt(8);
using int32_t = _BitInt(32);
using uint32_t = unsigned _BitInt(32);
using int64_t = _BitInt(64);
using uint64_t = unsigned _BitInt(64);
// NDArray indices are always `uint32_t`.
using NDIndex = uint32_t;
// The type of an index or a value describing the length of a range/slice is always `int32_t`.
using SliceIndex = int32_t;

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@ -1,75 +0,0 @@
#pragma once
#include "irrt/int_types.hpp"
#include "irrt/math_util.hpp"
extern "C" {
// Handle list assignment and dropping part of the list when
// both dest_step and src_step are +1.
// - All the index must *not* be out-of-bound or negative,
// - The end index is *inclusive*,
// - The length of src and dest slice size should already
// be checked: if dest.step == 1 then len(src) <= len(dest) else len(src) == len(dest)
SliceIndex __nac3_list_slice_assign_var_size(SliceIndex dest_start,
SliceIndex dest_end,
SliceIndex dest_step,
uint8_t* dest_arr,
SliceIndex dest_arr_len,
SliceIndex src_start,
SliceIndex src_end,
SliceIndex src_step,
uint8_t* src_arr,
SliceIndex src_arr_len,
const SliceIndex size) {
/* if dest_arr_len == 0, do nothing since we do not support extending list */
if (dest_arr_len == 0)
return dest_arr_len;
/* if both step is 1, memmove directly, handle the dropping of the list, and shrink size */
if (src_step == dest_step && dest_step == 1) {
const SliceIndex src_len = (src_end >= src_start) ? (src_end - src_start + 1) : 0;
const SliceIndex dest_len = (dest_end >= dest_start) ? (dest_end - dest_start + 1) : 0;
if (src_len > 0) {
__builtin_memmove(dest_arr + dest_start * size, src_arr + src_start * size, src_len * size);
}
if (dest_len > 0) {
/* dropping */
__builtin_memmove(dest_arr + (dest_start + src_len) * size, dest_arr + (dest_end + 1) * size,
(dest_arr_len - dest_end - 1) * size);
}
/* shrink size */
return dest_arr_len - (dest_len - src_len);
}
/* if two range overlaps, need alloca */
uint8_t need_alloca = (dest_arr == src_arr)
&& !(max(dest_start, dest_end) < min(src_start, src_end)
|| max(src_start, src_end) < min(dest_start, dest_end));
if (need_alloca) {
uint8_t* tmp = reinterpret_cast<uint8_t*>(__builtin_alloca(src_arr_len * size));
__builtin_memcpy(tmp, src_arr, src_arr_len * size);
src_arr = tmp;
}
SliceIndex src_ind = src_start;
SliceIndex dest_ind = dest_start;
for (; (src_step > 0) ? (src_ind <= src_end) : (src_ind >= src_end); src_ind += src_step, dest_ind += dest_step) {
/* for constant optimization */
if (size == 1) {
__builtin_memcpy(dest_arr + dest_ind, src_arr + src_ind, 1);
} else if (size == 4) {
__builtin_memcpy(dest_arr + dest_ind * 4, src_arr + src_ind * 4, 4);
} else if (size == 8) {
__builtin_memcpy(dest_arr + dest_ind * 8, src_arr + src_ind * 8, 8);
} else {
/* memcpy for var size, cannot overlap after previous alloca */
__builtin_memcpy(dest_arr + dest_ind * size, src_arr + src_ind * size, size);
}
}
/* only dest_step == 1 can we shrink the dest list. */
/* size should be ensured prior to calling this function */
if (dest_step == 1 && dest_end >= dest_start) {
__builtin_memmove(dest_arr + dest_ind * size, dest_arr + (dest_end + 1) * size,
(dest_arr_len - dest_end - 1) * size);
return dest_arr_len - (dest_end - dest_ind) - 1;
}
return dest_arr_len;
}
} // extern "C"

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@ -1,93 +0,0 @@
#pragma once
namespace {
// adapted from GNU Scientific Library: https://git.savannah.gnu.org/cgit/gsl.git/tree/sys/pow_int.c
// need to make sure `exp >= 0` before calling this function
template<typename T>
T __nac3_int_exp_impl(T base, T exp) {
T res = 1;
/* repeated squaring method */
do {
if (exp & 1) {
res *= base; /* for n odd */
}
exp >>= 1;
base *= base;
} while (exp);
return res;
}
} // namespace
#define DEF_nac3_int_exp_(T) \
T __nac3_int_exp_##T(T base, T exp) { \
return __nac3_int_exp_impl(base, exp); \
}
extern "C" {
// Putting semicolons here to make clang-format not reformat this into
// a stair shape.
DEF_nac3_int_exp_(int32_t);
DEF_nac3_int_exp_(int64_t);
DEF_nac3_int_exp_(uint32_t);
DEF_nac3_int_exp_(uint64_t);
int32_t __nac3_isinf(double x) {
return __builtin_isinf(x);
}
int32_t __nac3_isnan(double x) {
return __builtin_isnan(x);
}
double tgamma(double arg);
double __nac3_gamma(double z) {
// Handling for denormals
// | x | Python gamma(x) | C tgamma(x) |
// --- | ----------------- | --------------- | ----------- |
// (1) | nan | nan | nan |
// (2) | -inf | -inf | inf |
// (3) | inf | inf | inf |
// (4) | 0.0 | inf | inf |
// (5) | {-1.0, -2.0, ...} | inf | nan |
// (1)-(3)
if (__builtin_isinf(z) || __builtin_isnan(z)) {
return z;
}
double v = tgamma(z);
// (4)-(5)
return __builtin_isinf(v) || __builtin_isnan(v) ? __builtin_inf() : v;
}
double lgamma(double arg);
double __nac3_gammaln(double x) {
// libm's handling of value overflows differs from scipy:
// - scipy: gammaln(-inf) -> -inf
// - libm : lgamma(-inf) -> inf
if (__builtin_isinf(x)) {
return x;
}
return lgamma(x);
}
double j0(double x);
double __nac3_j0(double x) {
// libm's handling of value overflows differs from scipy:
// - scipy: j0(inf) -> nan
// - libm : j0(inf) -> 0.0
if (__builtin_isinf(x)) {
return __builtin_nan("");
}
return j0(x);
}
}

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@ -1,13 +0,0 @@
#pragma once
namespace {
template<typename T>
const T& max(const T& a, const T& b) {
return a > b ? a : b;
}
template<typename T>
const T& min(const T& a, const T& b) {
return a > b ? b : a;
}
} // namespace

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@ -1,144 +0,0 @@
#pragma once
#include "irrt/int_types.hpp"
namespace {
template<typename SizeT>
SizeT __nac3_ndarray_calc_size_impl(const SizeT* list_data, SizeT list_len, SizeT begin_idx, SizeT end_idx) {
__builtin_assume(end_idx <= list_len);
SizeT num_elems = 1;
for (SizeT i = begin_idx; i < end_idx; ++i) {
SizeT val = list_data[i];
__builtin_assume(val > 0);
num_elems *= val;
}
return num_elems;
}
template<typename SizeT>
void __nac3_ndarray_calc_nd_indices_impl(SizeT index, const SizeT* dims, SizeT num_dims, NDIndex* idxs) {
SizeT stride = 1;
for (SizeT dim = 0; dim < num_dims; dim++) {
SizeT i = num_dims - dim - 1;
__builtin_assume(dims[i] > 0);
idxs[i] = (index / stride) % dims[i];
stride *= dims[i];
}
}
template<typename SizeT>
SizeT __nac3_ndarray_flatten_index_impl(const SizeT* dims, SizeT num_dims, const NDIndex* indices, SizeT num_indices) {
SizeT idx = 0;
SizeT stride = 1;
for (SizeT i = 0; i < num_dims; ++i) {
SizeT ri = num_dims - i - 1;
if (ri < num_indices) {
idx += stride * indices[ri];
}
__builtin_assume(dims[i] > 0);
stride *= dims[ri];
}
return idx;
}
template<typename SizeT>
void __nac3_ndarray_calc_broadcast_impl(const SizeT* lhs_dims,
SizeT lhs_ndims,
const SizeT* rhs_dims,
SizeT rhs_ndims,
SizeT* out_dims) {
SizeT max_ndims = lhs_ndims > rhs_ndims ? lhs_ndims : rhs_ndims;
for (SizeT i = 0; i < max_ndims; ++i) {
const SizeT* lhs_dim_sz = i < lhs_ndims ? &lhs_dims[lhs_ndims - i - 1] : nullptr;
const SizeT* rhs_dim_sz = i < rhs_ndims ? &rhs_dims[rhs_ndims - i - 1] : nullptr;
SizeT* out_dim = &out_dims[max_ndims - i - 1];
if (lhs_dim_sz == nullptr) {
*out_dim = *rhs_dim_sz;
} else if (rhs_dim_sz == nullptr) {
*out_dim = *lhs_dim_sz;
} else if (*lhs_dim_sz == 1) {
*out_dim = *rhs_dim_sz;
} else if (*rhs_dim_sz == 1) {
*out_dim = *lhs_dim_sz;
} else if (*lhs_dim_sz == *rhs_dim_sz) {
*out_dim = *lhs_dim_sz;
} else {
__builtin_unreachable();
}
}
}
template<typename SizeT>
void __nac3_ndarray_calc_broadcast_idx_impl(const SizeT* src_dims,
SizeT src_ndims,
const NDIndex* in_idx,
NDIndex* out_idx) {
for (SizeT i = 0; i < src_ndims; ++i) {
SizeT src_i = src_ndims - i - 1;
out_idx[src_i] = src_dims[src_i] == 1 ? 0 : in_idx[src_i];
}
}
} // namespace
extern "C" {
uint32_t __nac3_ndarray_calc_size(const uint32_t* list_data, uint32_t list_len, uint32_t begin_idx, uint32_t end_idx) {
return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
}
uint64_t
__nac3_ndarray_calc_size64(const uint64_t* list_data, uint64_t list_len, uint64_t begin_idx, uint64_t end_idx) {
return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
}
void __nac3_ndarray_calc_nd_indices(uint32_t index, const uint32_t* dims, uint32_t num_dims, NDIndex* idxs) {
__nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
}
void __nac3_ndarray_calc_nd_indices64(uint64_t index, const uint64_t* dims, uint64_t num_dims, NDIndex* idxs) {
__nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
}
uint32_t
__nac3_ndarray_flatten_index(const uint32_t* dims, uint32_t num_dims, const NDIndex* indices, uint32_t num_indices) {
return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
}
uint64_t
__nac3_ndarray_flatten_index64(const uint64_t* dims, uint64_t num_dims, const NDIndex* indices, uint64_t num_indices) {
return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
}
void __nac3_ndarray_calc_broadcast(const uint32_t* lhs_dims,
uint32_t lhs_ndims,
const uint32_t* rhs_dims,
uint32_t rhs_ndims,
uint32_t* out_dims) {
return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
}
void __nac3_ndarray_calc_broadcast64(const uint64_t* lhs_dims,
uint64_t lhs_ndims,
const uint64_t* rhs_dims,
uint64_t rhs_ndims,
uint64_t* out_dims) {
return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
}
void __nac3_ndarray_calc_broadcast_idx(const uint32_t* src_dims,
uint32_t src_ndims,
const NDIndex* in_idx,
NDIndex* out_idx) {
__nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
}
void __nac3_ndarray_calc_broadcast_idx64(const uint64_t* src_dims,
uint64_t src_ndims,
const NDIndex* in_idx,
NDIndex* out_idx) {
__nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
}
}

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@ -1,28 +0,0 @@
#pragma once
#include "irrt/int_types.hpp"
extern "C" {
SliceIndex __nac3_slice_index_bound(SliceIndex i, const SliceIndex len) {
if (i < 0) {
i = len + i;
}
if (i < 0) {
return 0;
} else if (i > len) {
return len;
}
return i;
}
SliceIndex __nac3_range_slice_len(const SliceIndex start, const SliceIndex end, const SliceIndex step) {
SliceIndex diff = end - start;
if (diff > 0 && step > 0) {
return ((diff - 1) / step) + 1;
} else if (diff < 0 && step < 0) {
return ((diff + 1) / step) + 1;
} else {
return 0;
}
}
}

View File

@ -1,94 +1,26 @@
use inkwell::types::BasicTypeEnum;
use inkwell::values::{BasicValue, BasicValueEnum, IntValue, PointerValue};
use inkwell::values::BasicValueEnum;
use inkwell::{FloatPredicate, IntPredicate, OptimizationLevel};
use itertools::Itertools;
use crate::codegen::classes::{
ArrayLikeValue, NDArrayValue, ProxyValue, RangeValue, TypedArrayLikeAccessor,
UntypedArrayLikeAccessor, UntypedArrayLikeMutator,
};
use crate::codegen::expr::destructure_range;
use crate::codegen::irrt::calculate_len_for_slice_range;
use crate::codegen::macros::codegen_unreachable;
use crate::codegen::classes::{NDArrayValue, ProxyValue, UntypedArrayLikeAccessor};
use crate::codegen::numpy::ndarray_elementwise_unaryop_impl;
use crate::codegen::stmt::gen_for_callback_incrementing;
use crate::codegen::{extern_fns, irrt, llvm_intrinsics, numpy, CodeGenContext, CodeGenerator};
use crate::toplevel::helper::PrimDef;
use crate::toplevel::numpy::unpack_ndarray_var_tys;
use crate::typecheck::typedef::{Type, TypeEnum};
use crate::typecheck::typedef::Type;
/// Shorthand for [`unreachable!()`] when a type of argument is not supported.
///
/// The generated message will contain the function name and the name of the unsupported type.
fn unsupported_type(ctx: &CodeGenContext<'_, '_>, fn_name: &str, tys: &[Type]) -> ! {
codegen_unreachable!(
ctx,
unreachable!(
"{fn_name}() not supported for '{}'",
tys.iter().map(|ty| format!("'{}'", ctx.unifier.stringify(*ty))).join(", "),
)
}
/// Invokes the `len` builtin function.
pub fn call_len<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
n: (Type, BasicValueEnum<'ctx>),
) -> Result<IntValue<'ctx>, String> {
let llvm_i32 = ctx.ctx.i32_type();
let range_ty = ctx.primitives.range;
let (arg_ty, arg) = n;
Ok(if ctx.unifier.unioned(arg_ty, range_ty) {
let arg = RangeValue::from_ptr_val(arg.into_pointer_value(), Some("range"));
let (start, end, step) = destructure_range(ctx, arg);
calculate_len_for_slice_range(generator, ctx, start, end, step)
} else {
match &*ctx.unifier.get_ty_immutable(arg_ty) {
TypeEnum::TTuple { ty, .. } => llvm_i32.const_int(ty.len() as u64, false),
TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::List.id() => {
let zero = llvm_i32.const_zero();
let len = ctx
.build_gep_and_load(
arg.into_pointer_value(),
&[zero, llvm_i32.const_int(1, false)],
None,
)
.into_int_value();
ctx.builder.build_int_truncate_or_bit_cast(len, llvm_i32, "len").unwrap()
}
TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
let llvm_usize = generator.get_size_type(ctx.ctx);
let arg = NDArrayValue::from_ptr_val(arg.into_pointer_value(), llvm_usize, None);
let ndims = arg.dim_sizes().size(ctx, generator);
ctx.make_assert(
generator,
ctx.builder
.build_int_compare(IntPredicate::NE, ndims, llvm_usize.const_zero(), "")
.unwrap(),
"0:TypeError",
"len() of unsized object",
[None, None, None],
ctx.current_loc,
);
let len = unsafe {
arg.dim_sizes().get_typed_unchecked(
ctx,
generator,
&llvm_usize.const_zero(),
None,
)
};
ctx.builder.build_int_truncate_or_bit_cast(len, llvm_i32, "len").unwrap()
}
_ => codegen_unreachable!(ctx),
}
})
}
/// Invokes the `int32` builtin function.
pub fn call_int32<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
@ -99,6 +31,7 @@ pub fn call_int32<'ctx, G: CodeGenerator + ?Sized>(
let llvm_usize = generator.get_size_type(ctx.ctx);
let (n_ty, n) = n;
Ok(match n {
BasicValueEnum::IntValue(n) if matches!(n.get_type().get_bit_width(), 1 | 8) => {
debug_assert!(ctx.unifier.unioned(n_ty, ctx.primitives.bool));
@ -669,7 +602,7 @@ pub fn call_ceil<'ctx, G: CodeGenerator + ?Sized>(
ret_elem_ty,
None,
NDArrayValue::from_ptr_val(n, llvm_usize, None),
|generator, ctx, val| call_ceil(generator, ctx, (elem_ty, val), ret_elem_ty),
|generator, ctx, val| call_floor(generator, ctx, (elem_ty, val), ret_elem_ty),
)?;
ndarray.as_base_value().into()
@ -786,7 +719,7 @@ pub fn call_numpy_minimum<'ctx, G: CodeGenerator + ?Sized>(
} else if is_ndarray2 {
unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
} else {
codegen_unreachable!(ctx)
unreachable!()
};
let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
@ -890,7 +823,7 @@ pub fn call_numpy_max_min<'ctx, G: CodeGenerator + ?Sized>(
match fn_name {
"np_argmin" | "np_argmax" => llvm_int64.const_zero().into(),
"np_max" | "np_min" => a,
_ => codegen_unreachable!(ctx),
_ => unreachable!(),
}
}
BasicValueEnum::PointerValue(n)
@ -930,7 +863,6 @@ pub fn call_numpy_max_min<'ctx, G: CodeGenerator + ?Sized>(
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_int64.const_int(1, false),
(n_sz, false),
|generator, ctx, _, idx| {
@ -945,7 +877,7 @@ pub fn call_numpy_max_min<'ctx, G: CodeGenerator + ?Sized>(
"np_argmax" | "np_max" => {
call_max(ctx, (elem_ty, accumulator), (elem_ty, elem))
}
_ => codegen_unreachable!(ctx),
_ => unreachable!(),
};
let updated_idx = match (accumulator, result) {
@ -982,7 +914,7 @@ pub fn call_numpy_max_min<'ctx, G: CodeGenerator + ?Sized>(
match fn_name {
"np_argmin" | "np_argmax" => ctx.builder.build_load(res_idx, "").unwrap(),
"np_max" | "np_min" => ctx.builder.build_load(accumulator_addr, "").unwrap(),
_ => codegen_unreachable!(ctx),
_ => unreachable!(),
}
}
@ -1048,7 +980,7 @@ pub fn call_numpy_maximum<'ctx, G: CodeGenerator + ?Sized>(
} else if is_ndarray2 {
unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
} else {
codegen_unreachable!(ctx)
unreachable!()
};
let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
@ -1078,9 +1010,9 @@ pub fn call_numpy_maximum<'ctx, G: CodeGenerator + ?Sized>(
/// * `(arg_ty, arg_val)`: The [`Type`] and llvm value of the input argument.
/// * `fn_name`: The name of the function, only used when throwing an error with [`unsupported_type`]
/// * `get_ret_elem_type`: A function that takes in the input scalar [`Type`], and returns the function's return scalar [`Type`].
/// Return a constant [`Type`] here if the return type does not depend on the input type.
/// Return a constant [`Type`] here if the return type does not depend on the input type.
/// * `on_scalar`: The function that acts on the scalars of the input. Returns [`Option::None`]
/// if the scalar type & value are faulty and should panic with [`unsupported_type`].
/// if the scalar type & value are faulty and should panic with [`unsupported_type`].
fn helper_call_numpy_unary_elementwise<'ctx, OnScalarFn, RetElemFn, G>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
@ -1191,9 +1123,9 @@ pub fn call_abs<'ctx, G: CodeGenerator + ?Sized>(
/// * `$name:ident`: The identifier of the rust function to be generated.
/// * `$fn_name:literal`: To be passed to the `fn_name` parameter of [`helper_call_numpy_unary_elementwise`]
/// * `$get_ret_elem_type:expr`: To be passed to the `get_ret_elem_type` parameter of [`helper_call_numpy_unary_elementwise`].
/// But there is no need to make it a reference.
/// But there is no need to make it a reference.
/// * `$on_scalar:expr`: To be passed to the `on_scalar` parameter of [`helper_call_numpy_unary_elementwise`].
/// But there is no need to make it a reference.
/// But there is no need to make it a reference.
macro_rules! create_helper_call_numpy_unary_elementwise {
($name:ident, $fn_name:literal, $get_ret_elem_type:expr, $on_scalar:expr) => {
#[allow(clippy::redundant_closure_call)]
@ -1220,7 +1152,7 @@ macro_rules! create_helper_call_numpy_unary_elementwise {
/// * `$name:ident`: The identifier of the rust function to be generated.
/// * `$fn_name:literal`: To be passed to the `fn_name` parameter of [`helper_call_numpy_unary_elementwise`].
/// * `$on_scalar:expr`: The closure (see below for its type) that acts on float scalar values and returns
/// the boolean results of LLVM type `i1`. The returned `i1` value will be converted into an `i8`.
/// the boolean results of LLVM type `i1`. The returned `i1` value will be converted into an `i8`.
///
/// ```ignore
/// // Type of `$on_scalar:expr`
@ -1488,7 +1420,7 @@ pub fn call_numpy_arctan2<'ctx, G: CodeGenerator + ?Sized>(
} else if is_ndarray2 {
unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
} else {
codegen_unreachable!(ctx)
unreachable!()
};
let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
@ -1555,7 +1487,7 @@ pub fn call_numpy_copysign<'ctx, G: CodeGenerator + ?Sized>(
} else if is_ndarray2 {
unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
} else {
codegen_unreachable!(ctx)
unreachable!()
};
let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
@ -1622,7 +1554,7 @@ pub fn call_numpy_fmax<'ctx, G: CodeGenerator + ?Sized>(
} else if is_ndarray2 {
unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
} else {
codegen_unreachable!(ctx)
unreachable!()
};
let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
@ -1689,7 +1621,7 @@ pub fn call_numpy_fmin<'ctx, G: CodeGenerator + ?Sized>(
} else if is_ndarray2 {
unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
} else {
codegen_unreachable!(ctx)
unreachable!()
};
let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
@ -1812,7 +1744,7 @@ pub fn call_numpy_hypot<'ctx, G: CodeGenerator + ?Sized>(
} else if is_ndarray2 {
unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
} else {
codegen_unreachable!(ctx)
unreachable!()
};
let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
@ -1879,7 +1811,7 @@ pub fn call_numpy_nextafter<'ctx, G: CodeGenerator + ?Sized>(
} else if is_ndarray2 {
unpack_ndarray_var_tys(&mut ctx.unifier, x2_ty).0
} else {
codegen_unreachable!(ctx)
unreachable!()
};
let x1_scalar_ty = if is_ndarray1 { dtype } else { x1_ty };
@ -1903,501 +1835,3 @@ pub fn call_numpy_nextafter<'ctx, G: CodeGenerator + ?Sized>(
_ => unsupported_type(ctx, FN_NAME, &[x1_ty, x2_ty]),
})
}
/// Allocates a struct with the fields specified by `out_matrices` and returns a pointer to it
fn build_output_struct<'ctx>(
ctx: &mut CodeGenContext<'ctx, '_>,
out_matrices: Vec<BasicValueEnum<'ctx>>,
) -> PointerValue<'ctx> {
let field_ty =
out_matrices.iter().map(BasicValueEnum::get_type).collect::<Vec<BasicTypeEnum>>();
let out_ty = ctx.ctx.struct_type(&field_ty, false);
let out_ptr = ctx.builder.build_alloca(out_ty, "").unwrap();
for (i, v) in out_matrices.into_iter().enumerate() {
unsafe {
let ptr = ctx
.builder
.build_in_bounds_gep(
out_ptr,
&[
ctx.ctx.i32_type().const_zero(),
ctx.ctx.i32_type().const_int(i as u64, false),
],
"",
)
.unwrap();
ctx.builder.build_store(ptr, v).unwrap();
}
}
out_ptr
}
/// Invokes the `np_linalg_cholesky` linalg function
pub fn call_np_linalg_cholesky<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
x1: (Type, BasicValueEnum<'ctx>),
) -> Result<BasicValueEnum<'ctx>, String> {
const FN_NAME: &str = "np_linalg_cholesky";
let (x1_ty, x1) = x1;
let llvm_usize = generator.get_size_type(ctx.ctx);
if let BasicValueEnum::PointerValue(n1) = x1 {
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
unsupported_type(ctx, FN_NAME, &[x1_ty]);
};
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
let dim0 = unsafe {
n1.dim_sizes()
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
.into_int_value()
};
let dim1 = unsafe {
n1.dim_sizes()
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
.into_int_value()
};
let out = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim1])
.unwrap()
.as_base_value()
.as_basic_value_enum();
extern_fns::call_np_linalg_cholesky(ctx, x1, out, None);
Ok(out)
} else {
unsupported_type(ctx, FN_NAME, &[x1_ty])
}
}
/// Invokes the `np_linalg_qr` linalg function
pub fn call_np_linalg_qr<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
x1: (Type, BasicValueEnum<'ctx>),
) -> Result<BasicValueEnum<'ctx>, String> {
const FN_NAME: &str = "np_linalg_qr";
let (x1_ty, x1) = x1;
let llvm_usize = generator.get_size_type(ctx.ctx);
if let BasicValueEnum::PointerValue(n1) = x1 {
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
unimplemented!("{FN_NAME} operates on float type NdArrays only");
};
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
let dim0 = unsafe {
n1.dim_sizes()
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
.into_int_value()
};
let dim1 = unsafe {
n1.dim_sizes()
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
.into_int_value()
};
let k = llvm_intrinsics::call_int_smin(ctx, dim0, dim1, None);
let out_q = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, k])
.unwrap()
.as_base_value()
.as_basic_value_enum();
let out_r = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[k, dim1])
.unwrap()
.as_base_value()
.as_basic_value_enum();
extern_fns::call_np_linalg_qr(ctx, x1, out_q, out_r, None);
let out_ptr = build_output_struct(ctx, vec![out_q, out_r]);
Ok(ctx.builder.build_load(out_ptr, "QR_Factorization_result").map(Into::into).unwrap())
} else {
unsupported_type(ctx, FN_NAME, &[x1_ty])
}
}
/// Invokes the `np_linalg_svd` linalg function
pub fn call_np_linalg_svd<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
x1: (Type, BasicValueEnum<'ctx>),
) -> Result<BasicValueEnum<'ctx>, String> {
const FN_NAME: &str = "np_linalg_svd";
let (x1_ty, x1) = x1;
let llvm_usize = generator.get_size_type(ctx.ctx);
if let BasicValueEnum::PointerValue(n1) = x1 {
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
unsupported_type(ctx, FN_NAME, &[x1_ty]);
};
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
let dim0 = unsafe {
n1.dim_sizes()
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
.into_int_value()
};
let dim1 = unsafe {
n1.dim_sizes()
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
.into_int_value()
};
let k = llvm_intrinsics::call_int_smin(ctx, dim0, dim1, None);
let out_u = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
.unwrap()
.as_base_value()
.as_basic_value_enum();
let out_s = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[k])
.unwrap()
.as_base_value()
.as_basic_value_enum();
let out_vh = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim1, dim1])
.unwrap()
.as_base_value()
.as_basic_value_enum();
extern_fns::call_np_linalg_svd(ctx, x1, out_u, out_s, out_vh, None);
let out_ptr = build_output_struct(ctx, vec![out_u, out_s, out_vh]);
Ok(ctx.builder.build_load(out_ptr, "SVD_Factorization_result").map(Into::into).unwrap())
} else {
unsupported_type(ctx, FN_NAME, &[x1_ty])
}
}
/// Invokes the `np_linalg_inv` linalg function
pub fn call_np_linalg_inv<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
x1: (Type, BasicValueEnum<'ctx>),
) -> Result<BasicValueEnum<'ctx>, String> {
const FN_NAME: &str = "np_linalg_inv";
let (x1_ty, x1) = x1;
let llvm_usize = generator.get_size_type(ctx.ctx);
if let BasicValueEnum::PointerValue(n1) = x1 {
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
unsupported_type(ctx, FN_NAME, &[x1_ty]);
};
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
let dim0 = unsafe {
n1.dim_sizes()
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
.into_int_value()
};
let dim1 = unsafe {
n1.dim_sizes()
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
.into_int_value()
};
let out = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim1])
.unwrap()
.as_base_value()
.as_basic_value_enum();
extern_fns::call_np_linalg_inv(ctx, x1, out, None);
Ok(out)
} else {
unsupported_type(ctx, FN_NAME, &[x1_ty])
}
}
/// Invokes the `np_linalg_pinv` linalg function
pub fn call_np_linalg_pinv<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
x1: (Type, BasicValueEnum<'ctx>),
) -> Result<BasicValueEnum<'ctx>, String> {
const FN_NAME: &str = "np_linalg_pinv";
let (x1_ty, x1) = x1;
let llvm_usize = generator.get_size_type(ctx.ctx);
if let BasicValueEnum::PointerValue(n1) = x1 {
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
unsupported_type(ctx, FN_NAME, &[x1_ty]);
};
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
let dim0 = unsafe {
n1.dim_sizes()
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
.into_int_value()
};
let dim1 = unsafe {
n1.dim_sizes()
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
.into_int_value()
};
let out = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim1, dim0])
.unwrap()
.as_base_value()
.as_basic_value_enum();
extern_fns::call_np_linalg_pinv(ctx, x1, out, None);
Ok(out)
} else {
unsupported_type(ctx, FN_NAME, &[x1_ty])
}
}
/// Invokes the `sp_linalg_lu` linalg function
pub fn call_sp_linalg_lu<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
x1: (Type, BasicValueEnum<'ctx>),
) -> Result<BasicValueEnum<'ctx>, String> {
const FN_NAME: &str = "sp_linalg_lu";
let (x1_ty, x1) = x1;
let llvm_usize = generator.get_size_type(ctx.ctx);
if let BasicValueEnum::PointerValue(n1) = x1 {
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
unsupported_type(ctx, FN_NAME, &[x1_ty]);
};
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
let dim0 = unsafe {
n1.dim_sizes()
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
.into_int_value()
};
let dim1 = unsafe {
n1.dim_sizes()
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
.into_int_value()
};
let k = llvm_intrinsics::call_int_smin(ctx, dim0, dim1, None);
let out_l = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, k])
.unwrap()
.as_base_value()
.as_basic_value_enum();
let out_u = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[k, dim1])
.unwrap()
.as_base_value()
.as_basic_value_enum();
extern_fns::call_sp_linalg_lu(ctx, x1, out_l, out_u, None);
let out_ptr = build_output_struct(ctx, vec![out_l, out_u]);
Ok(ctx.builder.build_load(out_ptr, "LU_Factorization_result").map(Into::into).unwrap())
} else {
unsupported_type(ctx, FN_NAME, &[x1_ty])
}
}
/// Invokes the `np_linalg_matrix_power` linalg function
pub fn call_np_linalg_matrix_power<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
x1: (Type, BasicValueEnum<'ctx>),
x2: (Type, BasicValueEnum<'ctx>),
) -> Result<BasicValueEnum<'ctx>, String> {
const FN_NAME: &str = "np_linalg_matrix_power";
let (x1_ty, x1) = x1;
let (x2_ty, x2) = x2;
let x2 = call_float(generator, ctx, (x2_ty, x2)).unwrap();
let llvm_usize = generator.get_size_type(ctx.ctx);
if let (BasicValueEnum::PointerValue(n1), BasicValueEnum::FloatValue(n2)) = (x1, x2) {
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
unsupported_type(ctx, FN_NAME, &[x1_ty, x2_ty]);
};
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
// Changing second parameter to a `NDArray` for uniformity in function call
let n2_array = numpy::create_ndarray_const_shape(
generator,
ctx,
elem_ty,
&[llvm_usize.const_int(1, false)],
)
.unwrap();
unsafe {
n2_array.data().set_unchecked(
ctx,
generator,
&llvm_usize.const_zero(),
n2.as_basic_value_enum(),
);
};
let n2_array = n2_array.as_base_value().as_basic_value_enum();
let outdim0 = unsafe {
n1.dim_sizes()
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
.into_int_value()
};
let outdim1 = unsafe {
n1.dim_sizes()
.get_unchecked(ctx, generator, &llvm_usize.const_int(1, false), None)
.into_int_value()
};
let out = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[outdim0, outdim1])
.unwrap()
.as_base_value()
.as_basic_value_enum();
extern_fns::call_np_linalg_matrix_power(ctx, x1, n2_array, out, None);
Ok(out)
} else {
unsupported_type(ctx, FN_NAME, &[x1_ty, x2_ty])
}
}
/// Invokes the `np_linalg_det` linalg function
pub fn call_np_linalg_det<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
x1: (Type, BasicValueEnum<'ctx>),
) -> Result<BasicValueEnum<'ctx>, String> {
const FN_NAME: &str = "np_linalg_matrix_power";
let (x1_ty, x1) = x1;
let llvm_usize = generator.get_size_type(ctx.ctx);
if let BasicValueEnum::PointerValue(_) = x1 {
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
unsupported_type(ctx, FN_NAME, &[x1_ty]);
};
// Changing second parameter to a `NDArray` for uniformity in function call
let out = numpy::create_ndarray_const_shape(
generator,
ctx,
elem_ty,
&[llvm_usize.const_int(1, false)],
)
.unwrap();
extern_fns::call_np_linalg_det(ctx, x1, out.as_base_value().as_basic_value_enum(), None);
let res =
unsafe { out.data().get_unchecked(ctx, generator, &llvm_usize.const_zero(), None) };
Ok(res)
} else {
unsupported_type(ctx, FN_NAME, &[x1_ty])
}
}
/// Invokes the `sp_linalg_schur` linalg function
pub fn call_sp_linalg_schur<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
x1: (Type, BasicValueEnum<'ctx>),
) -> Result<BasicValueEnum<'ctx>, String> {
const FN_NAME: &str = "sp_linalg_schur";
let (x1_ty, x1) = x1;
let llvm_usize = generator.get_size_type(ctx.ctx);
if let BasicValueEnum::PointerValue(n1) = x1 {
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
unsupported_type(ctx, FN_NAME, &[x1_ty]);
};
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
let dim0 = unsafe {
n1.dim_sizes()
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
.into_int_value()
};
let out_t = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
.unwrap()
.as_base_value()
.as_basic_value_enum();
let out_z = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
.unwrap()
.as_base_value()
.as_basic_value_enum();
extern_fns::call_sp_linalg_schur(ctx, x1, out_t, out_z, None);
let out_ptr = build_output_struct(ctx, vec![out_t, out_z]);
Ok(ctx.builder.build_load(out_ptr, "Schur_Factorization_result").map(Into::into).unwrap())
} else {
unsupported_type(ctx, FN_NAME, &[x1_ty])
}
}
/// Invokes the `sp_linalg_hessenberg` linalg function
pub fn call_sp_linalg_hessenberg<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
x1: (Type, BasicValueEnum<'ctx>),
) -> Result<BasicValueEnum<'ctx>, String> {
const FN_NAME: &str = "sp_linalg_hessenberg";
let (x1_ty, x1) = x1;
let llvm_usize = generator.get_size_type(ctx.ctx);
if let BasicValueEnum::PointerValue(n1) = x1 {
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
let n1_elem_ty = ctx.get_llvm_type(generator, elem_ty);
let BasicTypeEnum::FloatType(_) = n1_elem_ty else {
unsupported_type(ctx, FN_NAME, &[x1_ty]);
};
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
let dim0 = unsafe {
n1.dim_sizes()
.get_unchecked(ctx, generator, &llvm_usize.const_zero(), None)
.into_int_value()
};
let out_h = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
.unwrap()
.as_base_value()
.as_basic_value_enum();
let out_q = numpy::create_ndarray_const_shape(generator, ctx, elem_ty, &[dim0, dim0])
.unwrap()
.as_base_value()
.as_basic_value_enum();
extern_fns::call_sp_linalg_hessenberg(ctx, x1, out_h, out_q, None);
let out_ptr = build_output_struct(ctx, vec![out_h, out_q]);
Ok(ctx
.builder
.build_load(out_ptr, "Hessenberg_decomposition_result")
.map(Into::into)
.unwrap())
} else {
unsupported_type(ctx, FN_NAME, &[x1_ty])
}
}

View File

@ -1404,7 +1404,7 @@ impl<'ctx> NDArrayValue<'ctx> {
/// Returns the double-indirection pointer to the `data` array, as if by calling `getelementptr`
/// on the field.
pub fn ptr_to_data(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
fn ptr_to_data(&self, ctx: &CodeGenContext<'ctx, '_>) -> PointerValue<'ctx> {
let llvm_i32 = ctx.ctx.i32_type();
let var_name = self.name.map(|v| format!("{v}.data.addr")).unwrap_or_default();
@ -1717,7 +1717,6 @@ impl<'ctx, Index: UntypedArrayLikeAccessor<'ctx>> ArrayLikeIndexer<'ctx, Index>
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_zero(),
(len, false),
|generator, ctx, _, i| {

View File

@ -25,7 +25,6 @@ pub struct ConcreteFuncArg {
pub name: StrRef,
pub ty: ConcreteType,
pub default_value: Option<SymbolValue>,
pub is_vararg: bool,
}
#[derive(Clone, Debug)]
@ -47,7 +46,6 @@ pub enum ConcreteTypeEnum {
TPrimitive(Primitive),
TTuple {
ty: Vec<ConcreteType>,
is_vararg_ctx: bool,
},
TObj {
obj_id: DefinitionId,
@ -104,16 +102,8 @@ impl ConcreteTypeStore {
.iter()
.map(|arg| ConcreteFuncArg {
name: arg.name,
ty: if arg.is_vararg {
let tuple_ty = unifier
.add_ty(TypeEnum::TTuple { ty: vec![arg.ty], is_vararg_ctx: true });
self.from_unifier_type(unifier, primitives, tuple_ty, cache)
} else {
self.from_unifier_type(unifier, primitives, arg.ty, cache)
},
ty: self.from_unifier_type(unifier, primitives, arg.ty, cache),
default_value: arg.default_value.clone(),
is_vararg: arg.is_vararg,
})
.collect(),
ret: self.from_unifier_type(unifier, primitives, signature.ret, cache),
@ -168,12 +158,11 @@ impl ConcreteTypeStore {
cache.insert(ty, None);
let ty_enum = unifier.get_ty(ty);
let result = match &*ty_enum {
TypeEnum::TTuple { ty, is_vararg_ctx } => ConcreteTypeEnum::TTuple {
TypeEnum::TTuple { ty } => ConcreteTypeEnum::TTuple {
ty: ty
.iter()
.map(|t| self.from_unifier_type(unifier, primitives, *t, cache))
.collect(),
is_vararg_ctx: *is_vararg_ctx,
},
TypeEnum::TObj { obj_id, fields, params } => ConcreteTypeEnum::TObj {
obj_id: *obj_id,
@ -259,12 +248,11 @@ impl ConcreteTypeStore {
*cache.get_mut(&cty).unwrap() = Some(ty);
return ty;
}
ConcreteTypeEnum::TTuple { ty, is_vararg_ctx } => TypeEnum::TTuple {
ConcreteTypeEnum::TTuple { ty } => TypeEnum::TTuple {
ty: ty
.iter()
.map(|cty| self.to_unifier_type(unifier, primitives, *cty, cache))
.collect(),
is_vararg_ctx: *is_vararg_ctx,
},
ConcreteTypeEnum::TVirtual { ty } => {
TypeEnum::TVirtual { ty: self.to_unifier_type(unifier, primitives, *ty, cache) }
@ -289,7 +277,6 @@ impl ConcreteTypeStore {
name: arg.name,
ty: self.to_unifier_type(unifier, primitives, arg.ty, cache),
default_value: arg.default_value.clone(),
is_vararg: false,
})
.collect(),
ret: self.to_unifier_type(unifier, primitives, *ret, cache),

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@ -13,11 +13,11 @@ use crate::codegen::CodeGenContext;
/// * `$extern_fn:literal`: Name of underlying extern function
///
/// Optional Arguments:
/// * `$(,$attributes:literal)*)`: Attributes linked with the extern function.
/// The default attributes are "mustprogress", "nofree", "nounwind", "willreturn", and "writeonly".
/// These will be used unless other attributes are specified
/// * `$(,$attributes:literal)*)`: Attributes linked with the extern function
/// The default attributes are "mustprogress", "nofree", "nounwind", "willreturn", and "writeonly"
/// These will be used unless other attributes are specified
/// * `$(,$args:ident)*`: Operands of the extern function
/// The data type of these operands will be set to `FloatValue`
/// The data type of these operands will be set to `FloatValue`
///
macro_rules! generate_extern_fn {
("unary", $fn_name:ident, $extern_fn:literal) => {
@ -130,62 +130,3 @@ pub fn call_ldexp<'ctx>(
.map(Either::unwrap_left)
.unwrap()
}
/// Macro to generate `np_linalg` and `sp_linalg` functions
/// The function takes as input `NDArray` and returns ()
///
/// Arguments:
/// * `$fn_name:ident`: The identifier of the rust function to be generated
/// * `$extern_fn:literal`: Name of underlying extern function
/// * (2/3/4): Number of `NDArray` that function takes as input
///
/// Note:
/// The operands and resulting `NDArray` are both passed as input to the funcion
/// It is the responsibility of caller to ensure that output `NDArray` is properly allocated on stack
/// The function changes the content of the output `NDArray` in-place
macro_rules! generate_linalg_extern_fn {
($fn_name:ident, $extern_fn:literal, 2) => {
generate_linalg_extern_fn!($fn_name, $extern_fn, mat1, mat2);
};
($fn_name:ident, $extern_fn:literal, 3) => {
generate_linalg_extern_fn!($fn_name, $extern_fn, mat1, mat2, mat3);
};
($fn_name:ident, $extern_fn:literal, 4) => {
generate_linalg_extern_fn!($fn_name, $extern_fn, mat1, mat2, mat3, mat4);
};
($fn_name:ident, $extern_fn:literal $(,$input_matrix:ident)*) => {
#[doc = concat!("Invokes the linalg `", stringify!($extern_fn), " function." )]
pub fn $fn_name<'ctx>(
ctx: &mut CodeGenContext<'ctx, '_>
$(,$input_matrix: BasicValueEnum<'ctx>)*,
name: Option<&str>,
){
const FN_NAME: &str = $extern_fn;
let extern_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
let fn_type = ctx.ctx.void_type().fn_type(&[$($input_matrix.get_type().into()),*], false);
let func = ctx.module.add_function(FN_NAME, fn_type, None);
for attr in ["mustprogress", "nofree", "nounwind", "willreturn", "writeonly"] {
func.add_attribute(
AttributeLoc::Function,
ctx.ctx.create_enum_attribute(Attribute::get_named_enum_kind_id(attr), 0),
);
}
func
});
ctx.builder.build_call(extern_fn, &[$($input_matrix.into(),)*], name.unwrap_or_default()).unwrap();
}
};
}
generate_linalg_extern_fn!(call_np_linalg_cholesky, "np_linalg_cholesky", 2);
generate_linalg_extern_fn!(call_np_linalg_qr, "np_linalg_qr", 3);
generate_linalg_extern_fn!(call_np_linalg_svd, "np_linalg_svd", 4);
generate_linalg_extern_fn!(call_np_linalg_inv, "np_linalg_inv", 2);
generate_linalg_extern_fn!(call_np_linalg_pinv, "np_linalg_pinv", 2);
generate_linalg_extern_fn!(call_np_linalg_matrix_power, "np_linalg_matrix_power", 3);
generate_linalg_extern_fn!(call_np_linalg_det, "np_linalg_det", 2);
generate_linalg_extern_fn!(call_sp_linalg_lu, "sp_linalg_lu", 3);
generate_linalg_extern_fn!(call_sp_linalg_schur, "sp_linalg_schur", 3);
generate_linalg_extern_fn!(call_sp_linalg_hessenberg, "sp_linalg_hessenberg", 3);

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@ -57,7 +57,6 @@ pub trait CodeGenerator {
/// - fun: Function signature, definition ID and the substitution key.
/// - params: Function parameters. Note that this does not include the object even if the
/// function is a class method.
///
/// Note that this function should check if the function is generated in another thread (due to
/// possible race condition), see the default implementation for an example.
fn gen_func_instance<'ctx>(
@ -124,45 +123,11 @@ pub trait CodeGenerator {
ctx: &mut CodeGenContext<'ctx, '_>,
target: &Expr<Option<Type>>,
value: ValueEnum<'ctx>,
value_ty: Type,
) -> Result<(), String>
where
Self: Sized,
{
gen_assign(self, ctx, target, value, value_ty)
}
/// Generate code for an assignment expression where LHS is a `"target_list"`.
///
/// See <https://docs.python.org/3/reference/simple_stmts.html#assignment-statements>.
fn gen_assign_target_list<'ctx>(
&mut self,
ctx: &mut CodeGenContext<'ctx, '_>,
targets: &Vec<Expr<Option<Type>>>,
value: ValueEnum<'ctx>,
value_ty: Type,
) -> Result<(), String>
where
Self: Sized,
{
gen_assign_target_list(self, ctx, targets, value, value_ty)
}
/// Generate code for an item assignment.
///
/// i.e., `target[key] = value`
fn gen_setitem<'ctx>(
&mut self,
ctx: &mut CodeGenContext<'ctx, '_>,
target: &Expr<Option<Type>>,
key: &Expr<Option<Type>>,
value: ValueEnum<'ctx>,
value_ty: Type,
) -> Result<(), String>
where
Self: Sized,
{
gen_setitem(self, ctx, target, key, value, value_ty)
gen_assign(self, ctx, target, value)
}
/// Generate code for a while expression.

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@ -0,0 +1,414 @@
using int8_t = _BitInt(8);
using uint8_t = unsigned _BitInt(8);
using int32_t = _BitInt(32);
using uint32_t = unsigned _BitInt(32);
using int64_t = _BitInt(64);
using uint64_t = unsigned _BitInt(64);
// NDArray indices are always `uint32_t`.
using NDIndex = uint32_t;
// The type of an index or a value describing the length of a range/slice is always `int32_t`.
using SliceIndex = int32_t;
namespace {
template <typename T>
const T& max(const T& a, const T& b) {
return a > b ? a : b;
}
template <typename T>
const T& min(const T& a, const T& b) {
return a > b ? b : a;
}
// adapted from GNU Scientific Library: https://git.savannah.gnu.org/cgit/gsl.git/tree/sys/pow_int.c
// need to make sure `exp >= 0` before calling this function
template <typename T>
T __nac3_int_exp_impl(T base, T exp) {
T res = 1;
/* repeated squaring method */
do {
if (exp & 1) {
res *= base; /* for n odd */
}
exp >>= 1;
base *= base;
} while (exp);
return res;
}
template <typename SizeT>
SizeT __nac3_ndarray_calc_size_impl(
const SizeT* list_data,
SizeT list_len,
SizeT begin_idx,
SizeT end_idx
) {
__builtin_assume(end_idx <= list_len);
SizeT num_elems = 1;
for (SizeT i = begin_idx; i < end_idx; ++i) {
SizeT val = list_data[i];
__builtin_assume(val > 0);
num_elems *= val;
}
return num_elems;
}
template <typename SizeT>
void __nac3_ndarray_calc_nd_indices_impl(
SizeT index,
const SizeT* dims,
SizeT num_dims,
NDIndex* idxs
) {
SizeT stride = 1;
for (SizeT dim = 0; dim < num_dims; dim++) {
SizeT i = num_dims - dim - 1;
__builtin_assume(dims[i] > 0);
idxs[i] = (index / stride) % dims[i];
stride *= dims[i];
}
}
template <typename SizeT>
SizeT __nac3_ndarray_flatten_index_impl(
const SizeT* dims,
SizeT num_dims,
const NDIndex* indices,
SizeT num_indices
) {
SizeT idx = 0;
SizeT stride = 1;
for (SizeT i = 0; i < num_dims; ++i) {
SizeT ri = num_dims - i - 1;
if (ri < num_indices) {
idx += stride * indices[ri];
}
__builtin_assume(dims[i] > 0);
stride *= dims[ri];
}
return idx;
}
template <typename SizeT>
void __nac3_ndarray_calc_broadcast_impl(
const SizeT* lhs_dims,
SizeT lhs_ndims,
const SizeT* rhs_dims,
SizeT rhs_ndims,
SizeT* out_dims
) {
SizeT max_ndims = lhs_ndims > rhs_ndims ? lhs_ndims : rhs_ndims;
for (SizeT i = 0; i < max_ndims; ++i) {
const SizeT* lhs_dim_sz = i < lhs_ndims ? &lhs_dims[lhs_ndims - i - 1] : nullptr;
const SizeT* rhs_dim_sz = i < rhs_ndims ? &rhs_dims[rhs_ndims - i - 1] : nullptr;
SizeT* out_dim = &out_dims[max_ndims - i - 1];
if (lhs_dim_sz == nullptr) {
*out_dim = *rhs_dim_sz;
} else if (rhs_dim_sz == nullptr) {
*out_dim = *lhs_dim_sz;
} else if (*lhs_dim_sz == 1) {
*out_dim = *rhs_dim_sz;
} else if (*rhs_dim_sz == 1) {
*out_dim = *lhs_dim_sz;
} else if (*lhs_dim_sz == *rhs_dim_sz) {
*out_dim = *lhs_dim_sz;
} else {
__builtin_unreachable();
}
}
}
template <typename SizeT>
void __nac3_ndarray_calc_broadcast_idx_impl(
const SizeT* src_dims,
SizeT src_ndims,
const NDIndex* in_idx,
NDIndex* out_idx
) {
for (SizeT i = 0; i < src_ndims; ++i) {
SizeT src_i = src_ndims - i - 1;
out_idx[src_i] = src_dims[src_i] == 1 ? 0 : in_idx[src_i];
}
}
} // namespace
extern "C" {
#define DEF_nac3_int_exp_(T) \
T __nac3_int_exp_##T(T base, T exp) {\
return __nac3_int_exp_impl(base, exp);\
}
DEF_nac3_int_exp_(int32_t)
DEF_nac3_int_exp_(int64_t)
DEF_nac3_int_exp_(uint32_t)
DEF_nac3_int_exp_(uint64_t)
SliceIndex __nac3_slice_index_bound(SliceIndex i, const SliceIndex len) {
if (i < 0) {
i = len + i;
}
if (i < 0) {
return 0;
} else if (i > len) {
return len;
}
return i;
}
SliceIndex __nac3_range_slice_len(
const SliceIndex start,
const SliceIndex end,
const SliceIndex step
) {
SliceIndex diff = end - start;
if (diff > 0 && step > 0) {
return ((diff - 1) / step) + 1;
} else if (diff < 0 && step < 0) {
return ((diff + 1) / step) + 1;
} else {
return 0;
}
}
// Handle list assignment and dropping part of the list when
// both dest_step and src_step are +1.
// - All the index must *not* be out-of-bound or negative,
// - The end index is *inclusive*,
// - The length of src and dest slice size should already
// be checked: if dest.step == 1 then len(src) <= len(dest) else len(src) == len(dest)
SliceIndex __nac3_list_slice_assign_var_size(
SliceIndex dest_start,
SliceIndex dest_end,
SliceIndex dest_step,
uint8_t* dest_arr,
SliceIndex dest_arr_len,
SliceIndex src_start,
SliceIndex src_end,
SliceIndex src_step,
uint8_t* src_arr,
SliceIndex src_arr_len,
const SliceIndex size
) {
/* if dest_arr_len == 0, do nothing since we do not support extending list */
if (dest_arr_len == 0) return dest_arr_len;
/* if both step is 1, memmove directly, handle the dropping of the list, and shrink size */
if (src_step == dest_step && dest_step == 1) {
const SliceIndex src_len = (src_end >= src_start) ? (src_end - src_start + 1) : 0;
const SliceIndex dest_len = (dest_end >= dest_start) ? (dest_end - dest_start + 1) : 0;
if (src_len > 0) {
__builtin_memmove(
dest_arr + dest_start * size,
src_arr + src_start * size,
src_len * size
);
}
if (dest_len > 0) {
/* dropping */
__builtin_memmove(
dest_arr + (dest_start + src_len) * size,
dest_arr + (dest_end + 1) * size,
(dest_arr_len - dest_end - 1) * size
);
}
/* shrink size */
return dest_arr_len - (dest_len - src_len);
}
/* if two range overlaps, need alloca */
uint8_t need_alloca =
(dest_arr == src_arr)
&& !(
max(dest_start, dest_end) < min(src_start, src_end)
|| max(src_start, src_end) < min(dest_start, dest_end)
);
if (need_alloca) {
uint8_t* tmp = reinterpret_cast<uint8_t *>(__builtin_alloca(src_arr_len * size));
__builtin_memcpy(tmp, src_arr, src_arr_len * size);
src_arr = tmp;
}
SliceIndex src_ind = src_start;
SliceIndex dest_ind = dest_start;
for (;
(src_step > 0) ? (src_ind <= src_end) : (src_ind >= src_end);
src_ind += src_step, dest_ind += dest_step
) {
/* for constant optimization */
if (size == 1) {
__builtin_memcpy(dest_arr + dest_ind, src_arr + src_ind, 1);
} else if (size == 4) {
__builtin_memcpy(dest_arr + dest_ind * 4, src_arr + src_ind * 4, 4);
} else if (size == 8) {
__builtin_memcpy(dest_arr + dest_ind * 8, src_arr + src_ind * 8, 8);
} else {
/* memcpy for var size, cannot overlap after previous alloca */
__builtin_memcpy(dest_arr + dest_ind * size, src_arr + src_ind * size, size);
}
}
/* only dest_step == 1 can we shrink the dest list. */
/* size should be ensured prior to calling this function */
if (dest_step == 1 && dest_end >= dest_start) {
__builtin_memmove(
dest_arr + dest_ind * size,
dest_arr + (dest_end + 1) * size,
(dest_arr_len - dest_end - 1) * size
);
return dest_arr_len - (dest_end - dest_ind) - 1;
}
return dest_arr_len;
}
int32_t __nac3_isinf(double x) {
return __builtin_isinf(x);
}
int32_t __nac3_isnan(double x) {
return __builtin_isnan(x);
}
double tgamma(double arg);
double __nac3_gamma(double z) {
// Handling for denormals
// | x | Python gamma(x) | C tgamma(x) |
// --- | ----------------- | --------------- | ----------- |
// (1) | nan | nan | nan |
// (2) | -inf | -inf | inf |
// (3) | inf | inf | inf |
// (4) | 0.0 | inf | inf |
// (5) | {-1.0, -2.0, ...} | inf | nan |
// (1)-(3)
if (__builtin_isinf(z) || __builtin_isnan(z)) {
return z;
}
double v = tgamma(z);
// (4)-(5)
return __builtin_isinf(v) || __builtin_isnan(v) ? __builtin_inf() : v;
}
double lgamma(double arg);
double __nac3_gammaln(double x) {
// libm's handling of value overflows differs from scipy:
// - scipy: gammaln(-inf) -> -inf
// - libm : lgamma(-inf) -> inf
if (__builtin_isinf(x)) {
return x;
}
return lgamma(x);
}
double j0(double x);
double __nac3_j0(double x) {
// libm's handling of value overflows differs from scipy:
// - scipy: j0(inf) -> nan
// - libm : j0(inf) -> 0.0
if (__builtin_isinf(x)) {
return __builtin_nan("");
}
return j0(x);
}
uint32_t __nac3_ndarray_calc_size(
const uint32_t* list_data,
uint32_t list_len,
uint32_t begin_idx,
uint32_t end_idx
) {
return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
}
uint64_t __nac3_ndarray_calc_size64(
const uint64_t* list_data,
uint64_t list_len,
uint64_t begin_idx,
uint64_t end_idx
) {
return __nac3_ndarray_calc_size_impl(list_data, list_len, begin_idx, end_idx);
}
void __nac3_ndarray_calc_nd_indices(
uint32_t index,
const uint32_t* dims,
uint32_t num_dims,
NDIndex* idxs
) {
__nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
}
void __nac3_ndarray_calc_nd_indices64(
uint64_t index,
const uint64_t* dims,
uint64_t num_dims,
NDIndex* idxs
) {
__nac3_ndarray_calc_nd_indices_impl(index, dims, num_dims, idxs);
}
uint32_t __nac3_ndarray_flatten_index(
const uint32_t* dims,
uint32_t num_dims,
const NDIndex* indices,
uint32_t num_indices
) {
return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
}
uint64_t __nac3_ndarray_flatten_index64(
const uint64_t* dims,
uint64_t num_dims,
const NDIndex* indices,
uint64_t num_indices
) {
return __nac3_ndarray_flatten_index_impl(dims, num_dims, indices, num_indices);
}
void __nac3_ndarray_calc_broadcast(
const uint32_t* lhs_dims,
uint32_t lhs_ndims,
const uint32_t* rhs_dims,
uint32_t rhs_ndims,
uint32_t* out_dims
) {
return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
}
void __nac3_ndarray_calc_broadcast64(
const uint64_t* lhs_dims,
uint64_t lhs_ndims,
const uint64_t* rhs_dims,
uint64_t rhs_ndims,
uint64_t* out_dims
) {
return __nac3_ndarray_calc_broadcast_impl(lhs_dims, lhs_ndims, rhs_dims, rhs_ndims, out_dims);
}
void __nac3_ndarray_calc_broadcast_idx(
const uint32_t* src_dims,
uint32_t src_ndims,
const NDIndex* in_idx,
NDIndex* out_idx
) {
__nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
}
void __nac3_ndarray_calc_broadcast_idx64(
const uint64_t* src_dims,
uint64_t src_ndims,
const NDIndex* in_idx,
NDIndex* out_idx
) {
__nac3_ndarray_calc_broadcast_idx_impl(src_dims, src_ndims, in_idx, out_idx);
}
} // extern "C"

View File

@ -1,29 +1,28 @@
use crate::{symbol_resolver::SymbolResolver, typecheck::typedef::Type};
use crate::typecheck::typedef::Type;
use super::{
classes::{
ArrayLikeIndexer, ArrayLikeValue, ArraySliceValue, ListValue, NDArrayValue,
TypedArrayLikeAccessor, TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
TypedArrayLikeAdapter, UntypedArrayLikeAccessor,
},
llvm_intrinsics,
macros::codegen_unreachable,
stmt::gen_for_callback_incrementing,
CodeGenContext, CodeGenerator,
llvm_intrinsics, CodeGenContext, CodeGenerator,
};
use crate::codegen::classes::TypedArrayLikeAccessor;
use crate::codegen::stmt::gen_for_callback_incrementing;
use inkwell::{
attributes::{Attribute, AttributeLoc},
context::Context,
memory_buffer::MemoryBuffer,
module::Module,
types::{BasicTypeEnum, IntType},
values::{BasicValue, BasicValueEnum, CallSiteValue, FloatValue, IntValue},
values::{BasicValueEnum, CallSiteValue, FloatValue, IntValue},
AddressSpace, IntPredicate,
};
use itertools::Either;
use nac3parser::ast::Expr;
#[must_use]
pub fn load_irrt<'ctx>(ctx: &'ctx Context, symbol_resolver: &dyn SymbolResolver) -> Module<'ctx> {
pub fn load_irrt(ctx: &Context) -> Module {
let bitcode_buf = MemoryBuffer::create_from_memory_range(
include_bytes!(concat!(env!("OUT_DIR"), "/irrt.bc")),
"irrt_bitcode_buffer",
@ -39,25 +38,6 @@ pub fn load_irrt<'ctx>(ctx: &'ctx Context, symbol_resolver: &dyn SymbolResolver)
let function = irrt_mod.get_function(symbol).unwrap();
function.add_attribute(AttributeLoc::Function, ctx.create_enum_attribute(inline_attr, 0));
}
// Initialize all global `EXN_*` exception IDs in IRRT with the [`SymbolResolver`].
let exn_id_type = ctx.i32_type();
let errors = &[
("EXN_INDEX_ERROR", "0:IndexError"),
("EXN_VALUE_ERROR", "0:ValueError"),
("EXN_ASSERTION_ERROR", "0:AssertionError"),
("EXN_TYPE_ERROR", "0:TypeError"),
];
for (irrt_name, symbol_name) in errors {
let exn_id = symbol_resolver.get_string_id(symbol_name);
let exn_id = exn_id_type.const_int(exn_id as u64, false).as_basic_value_enum();
let global = irrt_mod.get_global(irrt_name).unwrap_or_else(|| {
panic!("Exception symbol name '{irrt_name}' should exist in the IRRT LLVM module")
});
global.set_initializer(&exn_id);
}
irrt_mod
}
@ -75,7 +55,7 @@ pub fn integer_power<'ctx, G: CodeGenerator + ?Sized>(
(64, 64, true) => "__nac3_int_exp_int64_t",
(32, 32, false) => "__nac3_int_exp_uint32_t",
(64, 64, false) => "__nac3_int_exp_uint64_t",
_ => codegen_unreachable!(ctx),
_ => unreachable!(),
};
let base_type = base.get_type();
let pow_fun = ctx.module.get_function(symbol).unwrap_or_else(|| {
@ -461,7 +441,7 @@ pub fn list_slice_assignment<'ctx, G: CodeGenerator + ?Sized>(
BasicTypeEnum::IntType(t) => t.size_of(),
BasicTypeEnum::PointerType(t) => t.size_of(),
BasicTypeEnum::StructType(t) => t.size_of().unwrap(),
_ => codegen_unreachable!(ctx),
_ => unreachable!(),
};
ctx.builder.build_int_truncate_or_bit_cast(s, int32, "size").unwrap()
}
@ -588,8 +568,7 @@ pub fn call_j0<'ctx>(ctx: &CodeGenContext<'ctx, '_>, v: FloatValue<'ctx>) -> Flo
///
/// * `dims` - An [`ArrayLikeIndexer`] containing the size of each dimension.
/// * `range` - The dimension index to begin and end (exclusively) calculating the dimensions for,
/// or [`None`] if starting from the first dimension and ending at the last dimension
/// respectively.
/// or [`None`] if starting from the first dimension and ending at the last dimension respectively.
pub fn call_ndarray_calc_size<'ctx, G, Dims>(
generator: &G,
ctx: &CodeGenContext<'ctx, '_>,
@ -606,7 +585,7 @@ where
let ndarray_calc_size_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_calc_size",
64 => "__nac3_ndarray_calc_size64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
bw => unreachable!("Unsupported size type bit width: {}", bw),
};
let ndarray_calc_size_fn_t = llvm_usize.fn_type(
&[llvm_pusize.into(), llvm_usize.into(), llvm_usize.into(), llvm_usize.into()],
@ -641,7 +620,7 @@ where
///
/// * `index` - The index to compute the multidimensional index for.
/// * `ndarray` - LLVM pointer to the `NDArray`. This value must be the LLVM representation of an
/// `NDArray`.
/// `NDArray`.
pub fn call_ndarray_calc_nd_indices<'ctx, G: CodeGenerator + ?Sized>(
generator: &G,
ctx: &mut CodeGenContext<'ctx, '_>,
@ -657,7 +636,7 @@ pub fn call_ndarray_calc_nd_indices<'ctx, G: CodeGenerator + ?Sized>(
let ndarray_calc_nd_indices_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_calc_nd_indices",
64 => "__nac3_ndarray_calc_nd_indices64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
bw => unreachable!("Unsupported size type bit width: {}", bw),
};
let ndarray_calc_nd_indices_fn =
ctx.module.get_function(ndarray_calc_nd_indices_fn_name).unwrap_or_else(|| {
@ -726,7 +705,7 @@ where
let ndarray_flatten_index_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_flatten_index",
64 => "__nac3_ndarray_flatten_index64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
bw => unreachable!("Unsupported size type bit width: {}", bw),
};
let ndarray_flatten_index_fn =
ctx.module.get_function(ndarray_flatten_index_fn_name).unwrap_or_else(|| {
@ -765,7 +744,7 @@ where
/// multidimensional index.
///
/// * `ndarray` - LLVM pointer to the `NDArray`. This value must be the LLVM representation of an
/// `NDArray`.
/// `NDArray`.
/// * `indices` - The multidimensional index to compute the flattened index for.
pub fn call_ndarray_flatten_index<'ctx, G, Index>(
generator: &mut G,
@ -794,7 +773,7 @@ pub fn call_ndarray_calc_broadcast<'ctx, G: CodeGenerator + ?Sized>(
let ndarray_calc_broadcast_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_calc_broadcast",
64 => "__nac3_ndarray_calc_broadcast64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
bw => unreachable!("Unsupported size type bit width: {}", bw),
};
let ndarray_calc_broadcast_fn =
ctx.module.get_function(ndarray_calc_broadcast_fn_name).unwrap_or_else(|| {
@ -819,7 +798,6 @@ pub fn call_ndarray_calc_broadcast<'ctx, G: CodeGenerator + ?Sized>(
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_zero(),
(min_ndims, false),
|generator, ctx, _, idx| {
@ -914,7 +892,7 @@ pub fn call_ndarray_calc_broadcast_index<
let ndarray_calc_broadcast_fn_name = match llvm_usize.get_bit_width() {
32 => "__nac3_ndarray_calc_broadcast_idx",
64 => "__nac3_ndarray_calc_broadcast_idx64",
bw => codegen_unreachable!(ctx, "Unsupported size type bit width: {}", bw),
bw => unreachable!("Unsupported size type bit width: {}", bw),
};
let ndarray_calc_broadcast_fn =
ctx.module.get_function(ndarray_calc_broadcast_fn_name).unwrap_or_else(|| {

View File

@ -35,40 +35,6 @@ fn get_float_intrinsic_repr(ctx: &Context, ft: FloatType) -> &'static str {
unreachable!()
}
/// Invokes the [`llvm.va_start`](https://llvm.org/docs/LangRef.html#llvm-va-start-intrinsic)
/// intrinsic.
pub fn call_va_start<'ctx>(ctx: &CodeGenContext<'ctx, '_>, arglist: PointerValue<'ctx>) {
const FN_NAME: &str = "llvm.va_start";
let intrinsic_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
let llvm_void = ctx.ctx.void_type();
let llvm_i8 = ctx.ctx.i8_type();
let llvm_p0i8 = llvm_i8.ptr_type(AddressSpace::default());
let fn_type = llvm_void.fn_type(&[llvm_p0i8.into()], false);
ctx.module.add_function(FN_NAME, fn_type, None)
});
ctx.builder.build_call(intrinsic_fn, &[arglist.into()], "").unwrap();
}
/// Invokes the [`llvm.va_start`](https://llvm.org/docs/LangRef.html#llvm-va-start-intrinsic)
/// intrinsic.
pub fn call_va_end<'ctx>(ctx: &CodeGenContext<'ctx, '_>, arglist: PointerValue<'ctx>) {
const FN_NAME: &str = "llvm.va_end";
let intrinsic_fn = ctx.module.get_function(FN_NAME).unwrap_or_else(|| {
let llvm_void = ctx.ctx.void_type();
let llvm_i8 = ctx.ctx.i8_type();
let llvm_p0i8 = llvm_i8.ptr_type(AddressSpace::default());
let fn_type = llvm_void.fn_type(&[llvm_p0i8.into()], false);
ctx.module.add_function(FN_NAME, fn_type, None)
});
ctx.builder.build_call(intrinsic_fn, &[arglist.into()], "").unwrap();
}
/// Invokes the [`llvm.stacksave`](https://llvm.org/docs/LangRef.html#llvm-stacksave-intrinsic)
/// intrinsic.
pub fn call_stacksave<'ctx>(
@ -205,9 +171,8 @@ pub fn call_memcpy_generic<'ctx>(
/// * `$ctx:ident`: Reference to the current Code Generation Context
/// * `$name:ident`: Optional name to be assigned to the llvm build call (Option<&str>)
/// * `$llvm_name:literal`: Name of underlying llvm intrinsic function
/// * `$map_fn:ident`: Mapping function to be applied on `BasicValue` (`BasicValue` -> Function Return Type).
/// Use `BasicValueEnum::into_int_value` for Integer return type and
/// `BasicValueEnum::into_float_value` for Float return type
/// * `$map_fn:ident`: Mapping function to be applied on `BasicValue` (`BasicValue` -> Function Return Type)
/// Use `BasicValueEnum::into_int_value` for Integer return type and `BasicValueEnum::into_float_value` for Float return type
/// * `$llvm_ty:ident`: Type of first operand
/// * `,($val:ident)*`: Comma separated list of operands
macro_rules! generate_llvm_intrinsic_fn_body {
@ -223,8 +188,8 @@ macro_rules! generate_llvm_intrinsic_fn_body {
/// Arguments:
/// * `float/int`: Indicates the return and argument type of the function
/// * `$fn_name:ident`: The identifier of the rust function to be generated
/// * `$llvm_name:literal`: Name of underlying llvm intrinsic function.
/// Omit "llvm." prefix from the function name i.e. use "ceil" instead of "llvm.ceil"
/// * `$llvm_name:literal`: Name of underlying llvm intrinsic function
/// Omit "llvm." prefix from the function name i.e. use "ceil" instead of "llvm.ceil"
/// * `$val:ident`: The operand for unary operations
/// * `$val1:ident`, `$val2:ident`: The operands for binary operations
macro_rules! generate_llvm_intrinsic_fn {

View File

@ -50,22 +50,6 @@ mod test;
use concrete_type::{ConcreteType, ConcreteTypeEnum, ConcreteTypeStore};
pub use generator::{CodeGenerator, DefaultCodeGenerator};
mod macros {
/// Codegen-variant of [`std::unreachable`] which accepts an instance of [`CodeGenContext`] as
/// its first argument to provide Python source information to indicate the codegen location
/// causing the assertion.
macro_rules! codegen_unreachable {
($ctx:expr $(,)?) => {
std::unreachable!("unreachable code while processing {}", &$ctx.current_loc)
};
($ctx:expr, $($arg:tt)*) => {
std::unreachable!("unreachable code while processing {}: {}", &$ctx.current_loc, std::format!("{}", std::format_args!($($arg)+)))
};
}
pub(crate) use codegen_unreachable;
}
#[derive(Default)]
pub struct StaticValueStore {
pub lookup: HashMap<Vec<(usize, u64)>, usize>,
@ -84,16 +68,6 @@ pub struct CodeGenLLVMOptions {
pub target: CodeGenTargetMachineOptions,
}
impl CodeGenLLVMOptions {
/// Creates a [`TargetMachine`] using the target options specified by this struct.
///
/// See [`Target::create_target_machine`].
#[must_use]
pub fn create_target_machine(&self) -> Option<TargetMachine> {
self.target.create_target_machine(self.opt_level)
}
}
/// Additional options for code generation for the target machine.
#[derive(Clone, Debug, Eq, PartialEq)]
pub struct CodeGenTargetMachineOptions {
@ -364,10 +338,6 @@ impl WorkerRegistry {
let mut builder = context.create_builder();
let mut module = context.create_module(generator.get_name());
let target_machine = self.llvm_options.create_target_machine().unwrap();
module.set_data_layout(&target_machine.get_target_data().get_data_layout());
module.set_triple(&target_machine.get_triple());
module.add_basic_value_flag(
"Debug Info Version",
inkwell::module::FlagBehavior::Warning,
@ -391,10 +361,6 @@ impl WorkerRegistry {
errors.insert(e);
// create a new empty module just to continue codegen and collect errors
module = context.create_module(&format!("{}_recover", generator.get_name()));
let target_machine = self.llvm_options.create_target_machine().unwrap();
module.set_data_layout(&target_machine.get_target_data().get_data_layout());
module.set_triple(&target_machine.get_triple());
}
}
*self.task_count.lock() -= 1;
@ -460,7 +426,7 @@ pub struct CodeGenTask {
fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
ctx: &'ctx Context,
module: &Module<'ctx>,
generator: &G,
generator: &mut G,
unifier: &mut Unifier,
top_level: &TopLevelContext,
type_cache: &mut HashMap<Type, BasicTypeEnum<'ctx>>,
@ -554,10 +520,8 @@ fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
};
return ty;
}
TTuple { ty, is_vararg_ctx } => {
TTuple { ty } => {
// a struct with fields in the order present in the tuple
assert!(!is_vararg_ctx, "Tuples in vararg context must be instantiated with the correct number of arguments before calling get_llvm_type");
let fields = ty
.iter()
.map(|ty| {
@ -587,7 +551,7 @@ fn get_llvm_type<'ctx, G: CodeGenerator + ?Sized>(
fn get_llvm_abi_type<'ctx, G: CodeGenerator + ?Sized>(
ctx: &'ctx Context,
module: &Module<'ctx>,
generator: &G,
generator: &mut G,
unifier: &mut Unifier,
top_level: &TopLevelContext,
type_cache: &mut HashMap<Type, BasicTypeEnum<'ctx>>,
@ -596,11 +560,11 @@ fn get_llvm_abi_type<'ctx, G: CodeGenerator + ?Sized>(
) -> BasicTypeEnum<'ctx> {
// If the type is used in the definition of a function, return `i1` instead of `i8` for ABI
// consistency.
if unifier.unioned(ty, primitives.bool) {
return if unifier.unioned(ty, primitives.bool) {
ctx.bool_type().into()
} else {
get_llvm_type(ctx, module, generator, unifier, top_level, type_cache, ty)
}
};
}
/// Whether `sret` is needed for a return value with type `ty`.
@ -625,40 +589,6 @@ fn need_sret(ty: BasicTypeEnum) -> bool {
need_sret_impl(ty, true)
}
/// Returns the [`BasicTypeEnum`] representing a `va_list` struct for variadic arguments.
fn get_llvm_valist_type<'ctx>(ctx: &'ctx Context, triple: &TargetTriple) -> BasicTypeEnum<'ctx> {
let triple = TargetMachine::normalize_triple(triple);
let triple = triple.as_str().to_str().unwrap();
let arch = triple.split('-').next().unwrap();
let llvm_pi8 = ctx.i8_type().ptr_type(AddressSpace::default());
// Referenced from parseArch() in llvm/lib/Support/Triple.cpp
match arch {
"i386" | "i486" | "i586" | "i686" | "riscv32" => {
ctx.i8_type().ptr_type(AddressSpace::default()).into()
}
"amd64" | "x86_64" | "x86_64h" => {
let llvm_i32 = ctx.i32_type();
let va_list_tag = ctx.opaque_struct_type("struct.__va_list_tag");
va_list_tag.set_body(
&[llvm_i32.into(), llvm_i32.into(), llvm_pi8.into(), llvm_pi8.into()],
false,
);
va_list_tag.into()
}
"armv7" => {
let va_list = ctx.opaque_struct_type("struct.__va_list");
va_list.set_body(&[llvm_pi8.into()], false);
va_list.into()
}
triple => {
todo!("Unsupported platform for varargs: {triple}")
}
}
}
/// Implementation for generating LLVM IR for a function.
pub fn gen_func_impl<
'ctx,
@ -770,7 +700,6 @@ pub fn gen_func_impl<
name: arg.name,
ty: task.store.to_unifier_type(&mut unifier, &primitives, arg.ty, &mut cache),
default_value: arg.default_value.clone(),
is_vararg: arg.is_vararg,
})
.collect_vec(),
task.store.to_unifier_type(&mut unifier, &primitives, *ret, &mut cache),
@ -793,10 +722,7 @@ pub fn gen_func_impl<
let has_sret = ret_type.map_or(false, |ty| need_sret(ty));
let mut params = args
.iter()
.filter(|arg| !arg.is_vararg)
.map(|arg| {
debug_assert!(!arg.is_vararg);
get_llvm_abi_type(
context,
&module,
@ -815,12 +741,9 @@ pub fn gen_func_impl<
params.insert(0, ret_type.unwrap().ptr_type(AddressSpace::default()).into());
}
debug_assert!(matches!(args.iter().filter(|arg| arg.is_vararg).count(), 0..=1));
let vararg_arg = args.iter().find(|arg| arg.is_vararg);
let fn_type = match ret_type {
Some(ret_type) if !has_sret => ret_type.fn_type(&params, vararg_arg.is_some()),
_ => context.void_type().fn_type(&params, vararg_arg.is_some()),
Some(ret_type) if !has_sret => ret_type.fn_type(&params, false),
_ => context.void_type().fn_type(&params, false),
};
let symbol = &task.symbol_name;
@ -850,9 +773,7 @@ pub fn gen_func_impl<
let mut var_assignment = HashMap::new();
let offset = u32::from(has_sret);
// Store non-vararg argument values into local variables
for (n, arg) in args.iter().enumerate().filter(|(_, arg)| !arg.is_vararg) {
for (n, arg) in args.iter().enumerate() {
let param = fn_val.get_nth_param((n as u32) + offset).unwrap();
let local_type = get_llvm_type(
context,
@ -885,8 +806,6 @@ pub fn gen_func_impl<
var_assignment.insert(arg.name, (alloca, None, 0));
}
// TODO: Save vararg parameters as list
let return_buffer = if has_sret {
Some(fn_val.get_nth_param(0).unwrap().into_pointer_value())
} else {
@ -1109,9 +1028,3 @@ fn gen_in_range_check<'ctx>(
ctx.builder.build_int_compare(IntPredicate::SLT, lo, hi, "cmp").unwrap()
}
/// Returns the internal name for the `va_count` argument, used to indicate the number of arguments
/// passed to the variadic function.
fn get_va_count_arg_name(arg_name: StrRef) -> StrRef {
format!("__{}_va_count", &arg_name).into()
}

View File

@ -12,7 +12,6 @@ use crate::{
call_ndarray_calc_size,
},
llvm_intrinsics::{self, call_memcpy_generic},
macros::codegen_unreachable,
stmt::{gen_for_callback_incrementing, gen_for_range_callback, gen_if_else_expr_callback},
CodeGenContext, CodeGenerator,
},
@ -27,15 +26,12 @@ use crate::{
typedef::{FunSignature, Type, TypeEnum},
},
};
use inkwell::types::{AnyTypeEnum, BasicTypeEnum, PointerType};
use inkwell::{
types::BasicType,
values::{BasicValueEnum, IntValue, PointerValue},
AddressSpace, IntPredicate, OptimizationLevel,
};
use inkwell::{
types::{AnyTypeEnum, BasicTypeEnum, PointerType},
values::BasicValue,
};
use nac3parser::ast::{Operator, StrRef};
/// Creates an uninitialized `NDArray` instance.
@ -90,7 +86,6 @@ where
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_zero(),
(shape_len, false),
|generator, ctx, _, i| {
@ -136,7 +131,6 @@ where
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_zero(),
(shape_len, false),
|generator, ctx, _, i| {
@ -163,7 +157,7 @@ where
///
/// * `elem_ty` - The element type of the `NDArray`.
/// * `shape` - The shape of the `NDArray`, represented am array of [`IntValue`]s.
pub fn create_ndarray_const_shape<'ctx, G: CodeGenerator + ?Sized>(
fn create_ndarray_const_shape<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
elem_ty: Type,
@ -258,9 +252,9 @@ fn ndarray_zero_value<'ctx, G: CodeGenerator + ?Sized>(
} else if ctx.unifier.unioned(elem_ty, ctx.primitives.bool) {
ctx.ctx.bool_type().const_zero().into()
} else if ctx.unifier.unioned(elem_ty, ctx.primitives.str) {
ctx.gen_string(generator, "").into()
ctx.gen_string(generator, "")
} else {
codegen_unreachable!(ctx)
unreachable!()
}
}
@ -286,9 +280,9 @@ fn ndarray_one_value<'ctx, G: CodeGenerator + ?Sized>(
} else if ctx.unifier.unioned(elem_ty, ctx.primitives.bool) {
ctx.ctx.bool_type().const_int(1, false).into()
} else if ctx.unifier.unioned(elem_ty, ctx.primitives.str) {
ctx.gen_string(generator, "1").into()
ctx.gen_string(generator, "1")
} else {
codegen_unreachable!(ctx)
unreachable!()
}
}
@ -356,7 +350,7 @@ fn call_ndarray_empty_impl<'ctx, G: CodeGenerator + ?Sized>(
create_ndarray_const_shape(generator, ctx, elem_ty, &[shape_int])
}
_ => codegen_unreachable!(ctx),
_ => unreachable!(),
}
}
@ -388,7 +382,6 @@ where
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_zero(),
(ndarray_num_elems, false),
|generator, ctx, _, i| {
@ -627,7 +620,7 @@ fn call_ndarray_full_impl<'ctx, G: CodeGenerator + ?Sized>(
} else if fill_value.is_int_value() || fill_value.is_float_value() {
fill_value
} else {
codegen_unreachable!(ctx)
unreachable!()
};
Ok(value)
@ -710,12 +703,11 @@ fn ndarray_from_ndlist_impl<'ctx, G: CodeGenerator + ?Sized>(
gen_for_range_callback(
generator,
ctx,
None,
true,
|_, _| Ok(llvm_usize.const_zero()),
(|_, ctx| Ok(src_lst.load_size(ctx, None)), false),
|_, _| Ok(llvm_usize.const_int(1, false)),
|generator, ctx, _, i| {
|generator, ctx, i| {
let offset = ctx.builder.build_int_mul(stride, i, "").unwrap();
let dst_ptr =
@ -951,12 +943,11 @@ fn call_ndarray_array_impl<'ctx, G: CodeGenerator + ?Sized>(
gen_for_range_callback(
generator,
ctx,
None,
true,
|_, _| Ok(llvm_usize.const_zero()),
(|_, _| Ok(stop), false),
|_, _| Ok(llvm_usize.const_int(1, false)),
|generator, ctx, _, _| {
|generator, ctx, _| {
let plist_plist_i8 = make_llvm_list(llvm_plist_i8.into())
.ptr_type(AddressSpace::default());
@ -1072,15 +1063,15 @@ fn call_ndarray_eye_impl<'ctx, G: CodeGenerator + ?Sized>(
/// Copies a slice of an [`NDArrayValue`] to another.
///
/// - `dst_arr`: The [`NDArrayValue`] instance of the destination array. The `ndims` and `dim_sz`
/// fields should be populated before calling this function.
/// fields should be populated before calling this function.
/// - `dst_slice_ptr`: The [`PointerValue`] to the first element of the currently processing
/// dimensional slice in the destination array.
/// dimensional slice in the destination array.
/// - `src_arr`: The [`NDArrayValue`] instance of the source array.
/// - `src_slice_ptr`: The [`PointerValue`] to the first element of the currently processing
/// dimensional slice in the source array.
/// dimensional slice in the source array.
/// - `dim`: The index of the currently processing dimension.
/// - `slices`: List of all slices, with the first element corresponding to the slice applicable to
/// this dimension. The `start`/`stop` values of each slice must be non-negative indices.
/// this dimension. The `start`/`stop` values of each slice must be non-negative indices.
fn ndarray_sliced_copyto_impl<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
@ -1095,17 +1086,13 @@ fn ndarray_sliced_copyto_impl<'ctx, G: CodeGenerator + ?Sized>(
// If there are no (remaining) slice expressions, memcpy the entire dimension
if slices.is_empty() {
let sizeof_elem = ctx.get_llvm_type(generator, elem_ty).size_of().unwrap();
let stride = call_ndarray_calc_size(
generator,
ctx,
&src_arr.dim_sizes(),
(Some(llvm_usize.const_int(dim, false)), None),
);
let stride =
ctx.builder.build_int_z_extend_or_bit_cast(stride, sizeof_elem.get_type(), "").unwrap();
let sizeof_elem = ctx.get_llvm_type(generator, elem_ty).size_of().unwrap();
let cpy_len = ctx.builder.build_int_mul(stride, sizeof_elem, "").unwrap();
call_memcpy_generic(ctx, dst_slice_ptr, src_slice_ptr, cpy_len, llvm_i1.const_zero());
@ -1139,12 +1126,11 @@ fn ndarray_sliced_copyto_impl<'ctx, G: CodeGenerator + ?Sized>(
gen_for_range_callback(
generator,
ctx,
None,
false,
|_, _| Ok(start),
(|_, _| Ok(stop), true),
|_, _| Ok(step),
|generator, ctx, _, src_i| {
|generator, ctx, src_i| {
// Calculate the offset of the active slice
let src_data_offset = ctx.builder.build_int_mul(src_stride, src_i, "").unwrap();
let dst_i =
@ -1185,7 +1171,7 @@ fn ndarray_sliced_copyto_impl<'ctx, G: CodeGenerator + ?Sized>(
///
/// * `elem_ty` - The element type of the `NDArray`.
/// - `slices`: List of all slices, with the first element corresponding to the slice applicable to
/// this dimension. The `start`/`stop` values of each slice must be positive indices.
/// this dimension. The `start`/`stop` values of each slice must be positive indices.
pub fn ndarray_sliced_copy<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
@ -1257,7 +1243,6 @@ pub fn ndarray_sliced_copy<'ctx, G: CodeGenerator + ?Sized>(
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_int(slices.len() as u64, false),
(this.load_ndims(ctx), false),
|generator, ctx, _, idx| {
@ -1350,7 +1335,7 @@ where
///
/// * `elem_ty` - The element type of the `NDArray`.
/// * `res` - The `ndarray` instance to write results into, or [`None`] if the result should be
/// written to a new `ndarray`.
/// written to a new `ndarray`.
/// * `value_fn` - Function mapping the two input elements into the result.
///
/// # Panic
@ -1437,7 +1422,7 @@ where
///
/// * `elem_ty` - The element type of the `NDArray`.
/// * `res` - The `ndarray` instance to write results into, or [`None`] if the result should be
/// written to a new `ndarray`.
/// written to a new `ndarray`.
pub fn ndarray_matmul_2d<'ctx, G: CodeGenerator>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
@ -1662,7 +1647,6 @@ pub fn ndarray_matmul_2d<'ctx, G: CodeGenerator>(
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_i32.const_zero(),
(common_dim, false),
|generator, ctx, _, i| {
@ -2021,7 +2005,7 @@ pub fn gen_ndarray_fill<'ctx>(
} else if value_arg.is_int_value() || value_arg.is_float_value() {
value_arg
} else {
codegen_unreachable!(ctx)
unreachable!()
};
Ok(value)
@ -2030,497 +2014,3 @@ pub fn gen_ndarray_fill<'ctx>(
Ok(())
}
/// Generates LLVM IR for `ndarray.transpose`.
pub fn ndarray_transpose<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
x1: (Type, BasicValueEnum<'ctx>),
) -> Result<BasicValueEnum<'ctx>, String> {
const FN_NAME: &str = "ndarray_transpose";
let (x1_ty, x1) = x1;
let llvm_usize = generator.get_size_type(ctx.ctx);
if let BasicValueEnum::PointerValue(n1) = x1 {
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
let n_sz = call_ndarray_calc_size(generator, ctx, &n1.dim_sizes(), (None, None));
// Dimensions are reversed in the transposed array
let out = create_ndarray_dyn_shape(
generator,
ctx,
elem_ty,
&n1,
|_, ctx, n| Ok(n.load_ndims(ctx)),
|generator, ctx, n, idx| {
let new_idx = ctx.builder.build_int_sub(n.load_ndims(ctx), idx, "").unwrap();
let new_idx = ctx
.builder
.build_int_sub(new_idx, new_idx.get_type().const_int(1, false), "")
.unwrap();
unsafe { Ok(n.dim_sizes().get_typed_unchecked(ctx, generator, &new_idx, None)) }
},
)
.unwrap();
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_zero(),
(n_sz, false),
|generator, ctx, _, idx| {
let elem = unsafe { n1.data().get_unchecked(ctx, generator, &idx, None) };
let new_idx = generator.gen_var_alloc(ctx, llvm_usize.into(), None)?;
let rem_idx = generator.gen_var_alloc(ctx, llvm_usize.into(), None)?;
ctx.builder.build_store(new_idx, llvm_usize.const_zero()).unwrap();
ctx.builder.build_store(rem_idx, idx).unwrap();
// Incrementally calculate the new index in the transposed array
// For each index, we first decompose it into the n-dims and use those to reconstruct the new index
// The formula used for indexing is:
// idx = dim_n * ( ... (dim2 * (dim0 * dim1) + dim1) + dim2 ... ) + dim_n
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_zero(),
(n1.load_ndims(ctx), false),
|generator, ctx, _, ndim| {
let ndim_rev =
ctx.builder.build_int_sub(n1.load_ndims(ctx), ndim, "").unwrap();
let ndim_rev = ctx
.builder
.build_int_sub(ndim_rev, llvm_usize.const_int(1, false), "")
.unwrap();
let dim = unsafe {
n1.dim_sizes().get_typed_unchecked(ctx, generator, &ndim_rev, None)
};
let rem_idx_val =
ctx.builder.build_load(rem_idx, "").unwrap().into_int_value();
let new_idx_val =
ctx.builder.build_load(new_idx, "").unwrap().into_int_value();
let add_component =
ctx.builder.build_int_unsigned_rem(rem_idx_val, dim, "").unwrap();
let rem_idx_val =
ctx.builder.build_int_unsigned_div(rem_idx_val, dim, "").unwrap();
let new_idx_val = ctx.builder.build_int_mul(new_idx_val, dim, "").unwrap();
let new_idx_val =
ctx.builder.build_int_add(new_idx_val, add_component, "").unwrap();
ctx.builder.build_store(rem_idx, rem_idx_val).unwrap();
ctx.builder.build_store(new_idx, new_idx_val).unwrap();
Ok(())
},
llvm_usize.const_int(1, false),
)?;
let new_idx_val = ctx.builder.build_load(new_idx, "").unwrap().into_int_value();
unsafe { out.data().set_unchecked(ctx, generator, &new_idx_val, elem) };
Ok(())
},
llvm_usize.const_int(1, false),
)?;
Ok(out.as_base_value().into())
} else {
codegen_unreachable!(
ctx,
"{FN_NAME}() not supported for '{}'",
format!("'{}'", ctx.unifier.stringify(x1_ty))
)
}
}
/// LLVM-typed implementation for generating the implementation for `ndarray.reshape`.
///
/// * `x1` - `NDArray` to reshape.
/// * `shape` - The `shape` parameter used to construct the new `NDArray`.
/// Just like numpy, the `shape` argument can be:
/// 1. A list of `int32`; e.g., `np.reshape(arr, [600, -1, 3])`
/// 2. A tuple of `int32`; e.g., `np.reshape(arr, (-1, 800, 3))`
/// 3. A scalar `int32`; e.g., `np.reshape(arr, 3)`
///
/// Note that unlike other generating functions, one of the dimensions in the shape can be negative.
pub fn ndarray_reshape<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
x1: (Type, BasicValueEnum<'ctx>),
shape: (Type, BasicValueEnum<'ctx>),
) -> Result<BasicValueEnum<'ctx>, String> {
const FN_NAME: &str = "ndarray_reshape";
let (x1_ty, x1) = x1;
let (_, shape) = shape;
let llvm_usize = generator.get_size_type(ctx.ctx);
if let BasicValueEnum::PointerValue(n1) = x1 {
let (elem_ty, _) = unpack_ndarray_var_tys(&mut ctx.unifier, x1_ty);
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
let n_sz = call_ndarray_calc_size(generator, ctx, &n1.dim_sizes(), (None, None));
let acc = generator.gen_var_alloc(ctx, llvm_usize.into(), None)?;
let num_neg = generator.gen_var_alloc(ctx, llvm_usize.into(), None)?;
ctx.builder.build_store(acc, llvm_usize.const_int(1, false)).unwrap();
ctx.builder.build_store(num_neg, llvm_usize.const_zero()).unwrap();
let out = match shape {
BasicValueEnum::PointerValue(shape_list_ptr)
if ListValue::is_instance(shape_list_ptr, llvm_usize).is_ok() =>
{
// 1. A list of ints; e.g., `np.reshape(arr, [int64(600), int64(800, -1])`
let shape_list = ListValue::from_ptr_val(shape_list_ptr, llvm_usize, None);
// Check for -1 in dimensions
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_zero(),
(shape_list.load_size(ctx, None), false),
|generator, ctx, _, idx| {
let ele =
shape_list.data().get(ctx, generator, &idx, None).into_int_value();
let ele = ctx.builder.build_int_s_extend(ele, llvm_usize, "").unwrap();
gen_if_else_expr_callback(
generator,
ctx,
|_, ctx| {
Ok(ctx
.builder
.build_int_compare(
IntPredicate::SLT,
ele,
llvm_usize.const_zero(),
"",
)
.unwrap())
},
|_, ctx| -> Result<Option<IntValue>, String> {
let num_neg_value =
ctx.builder.build_load(num_neg, "").unwrap().into_int_value();
let num_neg_value = ctx
.builder
.build_int_add(
num_neg_value,
llvm_usize.const_int(1, false),
"",
)
.unwrap();
ctx.builder.build_store(num_neg, num_neg_value).unwrap();
Ok(None)
},
|_, ctx| {
let acc_value =
ctx.builder.build_load(acc, "").unwrap().into_int_value();
let acc_value =
ctx.builder.build_int_mul(acc_value, ele, "").unwrap();
ctx.builder.build_store(acc, acc_value).unwrap();
Ok(None)
},
)?;
Ok(())
},
llvm_usize.const_int(1, false),
)?;
let acc_val = ctx.builder.build_load(acc, "").unwrap().into_int_value();
let rem = ctx.builder.build_int_unsigned_div(n_sz, acc_val, "").unwrap();
// Generate the output shape by filling -1 with `rem`
create_ndarray_dyn_shape(
generator,
ctx,
elem_ty,
&shape_list,
|_, ctx, _| Ok(shape_list.load_size(ctx, None)),
|generator, ctx, shape_list, idx| {
let dim =
shape_list.data().get(ctx, generator, &idx, None).into_int_value();
let dim = ctx.builder.build_int_s_extend(dim, llvm_usize, "").unwrap();
Ok(gen_if_else_expr_callback(
generator,
ctx,
|_, ctx| {
Ok(ctx
.builder
.build_int_compare(
IntPredicate::SLT,
dim,
llvm_usize.const_zero(),
"",
)
.unwrap())
},
|_, _| Ok(Some(rem)),
|_, _| Ok(Some(dim)),
)?
.unwrap()
.into_int_value())
},
)
}
BasicValueEnum::StructValue(shape_tuple) => {
// 2. A tuple of `int32`; e.g., `np.reshape(arr, (-1, 800, 3))`
let ndims = shape_tuple.get_type().count_fields();
// Check for -1 in dims
for dim_i in 0..ndims {
let dim = ctx
.builder
.build_extract_value(shape_tuple, dim_i, "")
.unwrap()
.into_int_value();
let dim = ctx.builder.build_int_s_extend(dim, llvm_usize, "").unwrap();
gen_if_else_expr_callback(
generator,
ctx,
|_, ctx| {
Ok(ctx
.builder
.build_int_compare(
IntPredicate::SLT,
dim,
llvm_usize.const_zero(),
"",
)
.unwrap())
},
|_, ctx| -> Result<Option<IntValue>, String> {
let num_negs =
ctx.builder.build_load(num_neg, "").unwrap().into_int_value();
let num_negs = ctx
.builder
.build_int_add(num_negs, llvm_usize.const_int(1, false), "")
.unwrap();
ctx.builder.build_store(num_neg, num_negs).unwrap();
Ok(None)
},
|_, ctx| {
let acc_val = ctx.builder.build_load(acc, "").unwrap().into_int_value();
let acc_val = ctx.builder.build_int_mul(acc_val, dim, "").unwrap();
ctx.builder.build_store(acc, acc_val).unwrap();
Ok(None)
},
)?;
}
let acc_val = ctx.builder.build_load(acc, "").unwrap().into_int_value();
let rem = ctx.builder.build_int_unsigned_div(n_sz, acc_val, "").unwrap();
let mut shape = Vec::with_capacity(ndims as usize);
// Reconstruct shape filling negatives with rem
for dim_i in 0..ndims {
let dim = ctx
.builder
.build_extract_value(shape_tuple, dim_i, "")
.unwrap()
.into_int_value();
let dim = ctx.builder.build_int_s_extend(dim, llvm_usize, "").unwrap();
let dim = gen_if_else_expr_callback(
generator,
ctx,
|_, ctx| {
Ok(ctx
.builder
.build_int_compare(
IntPredicate::SLT,
dim,
llvm_usize.const_zero(),
"",
)
.unwrap())
},
|_, _| Ok(Some(rem)),
|_, _| Ok(Some(dim)),
)?
.unwrap()
.into_int_value();
shape.push(dim);
}
create_ndarray_const_shape(generator, ctx, elem_ty, shape.as_slice())
}
BasicValueEnum::IntValue(shape_int) => {
// 3. A scalar `int32`; e.g., `np.reshape(arr, 3)`
let shape_int = gen_if_else_expr_callback(
generator,
ctx,
|_, ctx| {
Ok(ctx
.builder
.build_int_compare(
IntPredicate::SLT,
shape_int,
llvm_usize.const_zero(),
"",
)
.unwrap())
},
|_, _| Ok(Some(n_sz)),
|_, ctx| {
Ok(Some(ctx.builder.build_int_s_extend(shape_int, llvm_usize, "").unwrap()))
},
)?
.unwrap()
.into_int_value();
create_ndarray_const_shape(generator, ctx, elem_ty, &[shape_int])
}
_ => codegen_unreachable!(ctx),
}
.unwrap();
// Only allow one dimension to be negative
let num_negs = ctx.builder.build_load(num_neg, "").unwrap().into_int_value();
ctx.make_assert(
generator,
ctx.builder
.build_int_compare(IntPredicate::ULT, num_negs, llvm_usize.const_int(2, false), "")
.unwrap(),
"0:ValueError",
"can only specify one unknown dimension",
[None, None, None],
ctx.current_loc,
);
// The new shape must be compatible with the old shape
let out_sz = call_ndarray_calc_size(generator, ctx, &out.dim_sizes(), (None, None));
ctx.make_assert(
generator,
ctx.builder.build_int_compare(IntPredicate::EQ, out_sz, n_sz, "").unwrap(),
"0:ValueError",
"cannot reshape array of size {0} into provided shape of size {1}",
[Some(n_sz), Some(out_sz), None],
ctx.current_loc,
);
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_zero(),
(n_sz, false),
|generator, ctx, _, idx| {
let elem = unsafe { n1.data().get_unchecked(ctx, generator, &idx, None) };
unsafe { out.data().set_unchecked(ctx, generator, &idx, elem) };
Ok(())
},
llvm_usize.const_int(1, false),
)?;
Ok(out.as_base_value().into())
} else {
codegen_unreachable!(
ctx,
"{FN_NAME}() not supported for '{}'",
format!("'{}'", ctx.unifier.stringify(x1_ty))
)
}
}
/// Generates LLVM IR for `ndarray.dot`.
/// Calculate inner product of two vectors or literals
/// For matrix multiplication use `np_matmul`
///
/// The input `NDArray` are flattened and treated as 1D
/// The operation is equivalent to `np.dot(arr1.ravel(), arr2.ravel())`
pub fn ndarray_dot<'ctx, G: CodeGenerator + ?Sized>(
generator: &mut G,
ctx: &mut CodeGenContext<'ctx, '_>,
x1: (Type, BasicValueEnum<'ctx>),
x2: (Type, BasicValueEnum<'ctx>),
) -> Result<BasicValueEnum<'ctx>, String> {
const FN_NAME: &str = "ndarray_dot";
let (x1_ty, x1) = x1;
let (_, x2) = x2;
let llvm_usize = generator.get_size_type(ctx.ctx);
match (x1, x2) {
(BasicValueEnum::PointerValue(n1), BasicValueEnum::PointerValue(n2)) => {
let n1 = NDArrayValue::from_ptr_val(n1, llvm_usize, None);
let n2 = NDArrayValue::from_ptr_val(n2, llvm_usize, None);
let n1_sz = call_ndarray_calc_size(generator, ctx, &n1.dim_sizes(), (None, None));
let n2_sz = call_ndarray_calc_size(generator, ctx, &n1.dim_sizes(), (None, None));
ctx.make_assert(
generator,
ctx.builder.build_int_compare(IntPredicate::EQ, n1_sz, n2_sz, "").unwrap(),
"0:ValueError",
"shapes ({0}), ({1}) not aligned",
[Some(n1_sz), Some(n2_sz), None],
ctx.current_loc,
);
let identity =
unsafe { n1.data().get_unchecked(ctx, generator, &llvm_usize.const_zero(), None) };
let acc = ctx.builder.build_alloca(identity.get_type(), "").unwrap();
ctx.builder.build_store(acc, identity.get_type().const_zero()).unwrap();
gen_for_callback_incrementing(
generator,
ctx,
None,
llvm_usize.const_zero(),
(n1_sz, false),
|generator, ctx, _, idx| {
let elem1 = unsafe { n1.data().get_unchecked(ctx, generator, &idx, None) };
let elem2 = unsafe { n2.data().get_unchecked(ctx, generator, &idx, None) };
let product = match elem1 {
BasicValueEnum::IntValue(e1) => ctx
.builder
.build_int_mul(e1, elem2.into_int_value(), "")
.unwrap()
.as_basic_value_enum(),
BasicValueEnum::FloatValue(e1) => ctx
.builder
.build_float_mul(e1, elem2.into_float_value(), "")
.unwrap()
.as_basic_value_enum(),
_ => codegen_unreachable!(ctx),
};
let acc_val = ctx.builder.build_load(acc, "").unwrap();
let acc_val = match acc_val {
BasicValueEnum::IntValue(e1) => ctx
.builder
.build_int_add(e1, product.into_int_value(), "")
.unwrap()
.as_basic_value_enum(),
BasicValueEnum::FloatValue(e1) => ctx
.builder
.build_float_add(e1, product.into_float_value(), "")
.unwrap()
.as_basic_value_enum(),
_ => codegen_unreachable!(ctx),
};
ctx.builder.build_store(acc, acc_val).unwrap();
Ok(())
},
llvm_usize.const_int(1, false),
)?;
let acc_val = ctx.builder.build_load(acc, "").unwrap();
Ok(acc_val)
}
(BasicValueEnum::IntValue(e1), BasicValueEnum::IntValue(e2)) => {
Ok(ctx.builder.build_int_mul(e1, e2, "").unwrap().as_basic_value_enum())
}
(BasicValueEnum::FloatValue(e1), BasicValueEnum::FloatValue(e2)) => {
Ok(ctx.builder.build_float_mul(e1, e2, "").unwrap().as_basic_value_enum())
}
_ => codegen_unreachable!(
ctx,
"{FN_NAME}() not supported for '{}'",
format!("'{}'", ctx.unifier.stringify(x1_ty))
),
}
}

File diff suppressed because it is too large Load Diff

View File

@ -94,7 +94,7 @@ fn test_primitives() {
"};
let statements = parse_program(source, FileName::default()).unwrap();
let composer = TopLevelComposer::new(Vec::new(), Vec::new(), ComposerConfig::default(), 32).0;
let composer = TopLevelComposer::new(Vec::new(), ComposerConfig::default(), 32).0;
let mut unifier = composer.unifier.clone();
let primitives = composer.primitives_ty;
let top_level = Arc::new(composer.make_top_level_context());
@ -109,18 +109,8 @@ fn test_primitives() {
let threads = vec![DefaultCodeGenerator::new("test".into(), 32).into()];
let signature = FunSignature {
args: vec![
FuncArg {
name: "a".into(),
ty: primitives.int32,
default_value: None,
is_vararg: false,
},
FuncArg {
name: "b".into(),
ty: primitives.int32,
default_value: None,
is_vararg: false,
},
FuncArg { name: "a".into(), ty: primitives.int32, default_value: None },
FuncArg { name: "b".into(), ty: primitives.int32, default_value: None },
],
ret: primitives.int32,
vars: VarMap::new(),
@ -199,8 +189,6 @@ fn test_primitives() {
let expected = indoc! {"
; ModuleID = 'test'
source_filename = \"test\"
target datalayout = \"e-m:e-p270:32:32-p271:32:32-p272:64:64-i64:64-f80:128-n8:16:32:64-S128\"
target triple = \"x86_64-unknown-linux-gnu\"
; Function Attrs: mustprogress nofree norecurse nosync nounwind readnone willreturn
define i32 @testing(i32 %0, i32 %1) local_unnamed_addr #0 !dbg !4 {
@ -258,19 +246,14 @@ fn test_simple_call() {
"};
let statements_2 = parse_program(source_2, FileName::default()).unwrap();
let composer = TopLevelComposer::new(Vec::new(), Vec::new(), ComposerConfig::default(), 32).0;
let composer = TopLevelComposer::new(Vec::new(), ComposerConfig::default(), 32).0;
let mut unifier = composer.unifier.clone();
let primitives = composer.primitives_ty;
let top_level = Arc::new(composer.make_top_level_context());
unifier.top_level = Some(top_level.clone());
let signature = FunSignature {
args: vec![FuncArg {
name: "a".into(),
ty: primitives.int32,
default_value: None,
is_vararg: false,
}],
args: vec![FuncArg { name: "a".into(), ty: primitives.int32, default_value: None }],
ret: primitives.int32,
vars: VarMap::new(),
};
@ -385,8 +368,6 @@ fn test_simple_call() {
let expected = indoc! {"
; ModuleID = 'test'
source_filename = \"test\"
target datalayout = \"e-m:e-p270:32:32-p271:32:32-p272:64:64-i64:64-f80:128-n8:16:32:64-S128\"
target triple = \"x86_64-unknown-linux-gnu\"
; Function Attrs: mustprogress nofree norecurse nosync nounwind readnone willreturn
define i32 @testing(i32 %0) local_unnamed_addr #0 !dbg !5 {

View File

@ -78,14 +78,14 @@ impl SymbolValue {
}
Constant::Tuple(t) => {
let expected_ty = unifier.get_ty(expected_ty);
let TypeEnum::TTuple { ty, is_vararg_ctx } = expected_ty.as_ref() else {
let TypeEnum::TTuple { ty } = expected_ty.as_ref() else {
return Err(format!(
"Expected {:?}, but got Tuple",
expected_ty.get_type_name()
));
};
assert!(*is_vararg_ctx || ty.len() == t.len());
assert_eq!(ty.len(), t.len());
let elems = t
.iter()
@ -155,7 +155,7 @@ impl SymbolValue {
SymbolValue::Bool(_) => primitives.bool,
SymbolValue::Tuple(vs) => {
let vs_tys = vs.iter().map(|v| v.get_type(primitives, unifier)).collect::<Vec<_>>();
unifier.add_ty(TypeEnum::TTuple { ty: vs_tys, is_vararg_ctx: false })
unifier.add_ty(TypeEnum::TTuple { ty: vs_tys })
}
SymbolValue::OptionSome(_) | SymbolValue::OptionNone => primitives.option,
}
@ -482,7 +482,7 @@ pub fn parse_type_annotation<T>(
parse_type_annotation(resolver, top_level_defs, unifier, primitives, elt)
})
.collect::<Result<Vec<_>, _>>()?;
Ok(unifier.add_ty(TypeEnum::TTuple { ty, is_vararg_ctx: false }))
Ok(unifier.add_ty(TypeEnum::TTuple { ty }))
} else {
Err(HashSet::from(["Expected multiple elements for tuple".into()]))
}

View File

@ -14,7 +14,9 @@ use strum::IntoEnumIterator;
use crate::{
codegen::{
builtin_fns,
classes::{ProxyValue, RangeValue},
classes::{ArrayLikeValue, NDArrayValue, ProxyValue, RangeValue, TypedArrayLikeAccessor},
expr::destructure_range,
irrt::*,
numpy::*,
stmt::exn_constructor,
},
@ -43,26 +45,10 @@ pub fn get_exn_constructor(
name: "msg".into(),
ty: string,
default_value: Some(SymbolValue::Str(String::new())),
is_vararg: false,
},
FuncArg {
name: "param0".into(),
ty: int64,
default_value: Some(SymbolValue::I64(0)),
is_vararg: false,
},
FuncArg {
name: "param1".into(),
ty: int64,
default_value: Some(SymbolValue::I64(0)),
is_vararg: false,
},
FuncArg {
name: "param2".into(),
ty: int64,
default_value: Some(SymbolValue::I64(0)),
is_vararg: false,
},
FuncArg { name: "param0".into(), ty: int64, default_value: Some(SymbolValue::I64(0)) },
FuncArg { name: "param1".into(), ty: int64, default_value: Some(SymbolValue::I64(0)) },
FuncArg { name: "param2".into(), ty: int64, default_value: Some(SymbolValue::I64(0)) },
];
let exn_type = unifier.add_ty(TypeEnum::TObj {
obj_id: DefinitionId(class_id),
@ -112,7 +98,7 @@ pub fn get_exn_constructor(
/// * `name`: The name of the implemented NumPy function.
/// * `ret_ty`: The return type of this function.
/// * `param_ty`: The parameters accepted by this function, represented by a tuple of the
/// [parameter type][Type] and the parameter symbol name.
/// [parameter type][Type] and the parameter symbol name.
/// * `codegen_callback`: A lambda generating LLVM IR for the implementation of this function.
fn create_fn_by_codegen(
unifier: &mut Unifier,
@ -128,12 +114,7 @@ fn create_fn_by_codegen(
signature: unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: param_ty
.iter()
.map(|p| FuncArg {
name: p.1.into(),
ty: p.0,
default_value: None,
is_vararg: false,
})
.map(|p| FuncArg { name: p.1.into(), ty: p.0, default_value: None })
.collect(),
ret: ret_ty,
vars: var_map.clone(),
@ -152,7 +133,7 @@ fn create_fn_by_codegen(
/// * `name`: The name of the implemented NumPy function.
/// * `ret_ty`: The return type of this function.
/// * `param_ty`: The parameters accepted by this function, represented by a tuple of the
/// [parameter type][Type] and the parameter symbol name.
/// [parameter type][Type] and the parameter symbol name.
/// * `intrinsic_fn`: The fully-qualified name of the LLVM intrinsic function.
fn create_fn_by_intrinsic(
unifier: &mut Unifier,
@ -214,10 +195,10 @@ fn create_fn_by_intrinsic(
/// * `name`: The name of the implemented NumPy function.
/// * `ret_ty`: The return type of this function.
/// * `param_ty`: The parameters accepted by this function, represented by a tuple of the
/// [parameter type][Type] and the parameter symbol name.
/// [parameter type][Type] and the parameter symbol name.
/// * `extern_fn`: The fully-qualified name of the extern function used as the implementation.
/// * `attrs`: The list of attributes to apply to this function declaration. Note that `nounwind` is
/// already implied by the C ABI.
/// already implied by the C ABI.
fn create_fn_by_extern(
unifier: &mut Unifier,
var_map: &VarMap,
@ -365,8 +346,8 @@ impl<'a> BuiltinBuilder<'a> {
let (is_some_ty, unwrap_ty, option_tvar) =
if let TypeEnum::TObj { fields, params, .. } = unifier.get_ty(option).as_ref() {
(
*fields.get(&PrimDef::FunOptionIsSome.simple_name().into()).unwrap(),
*fields.get(&PrimDef::FunOptionUnwrap.simple_name().into()).unwrap(),
*fields.get(&PrimDef::OptionIsSome.simple_name().into()).unwrap(),
*fields.get(&PrimDef::OptionUnwrap.simple_name().into()).unwrap(),
iter_type_vars(params).next().unwrap(),
)
} else {
@ -381,9 +362,9 @@ impl<'a> BuiltinBuilder<'a> {
let ndarray_dtype_tvar = iter_type_vars(ndarray_params).next().unwrap();
let ndarray_ndims_tvar = iter_type_vars(ndarray_params).nth(1).unwrap();
let ndarray_copy_ty =
*ndarray_fields.get(&PrimDef::FunNDArrayCopy.simple_name().into()).unwrap();
*ndarray_fields.get(&PrimDef::NDArrayCopy.simple_name().into()).unwrap();
let ndarray_fill_ty =
*ndarray_fields.get(&PrimDef::FunNDArrayFill.simple_name().into()).unwrap();
*ndarray_fields.get(&PrimDef::NDArrayFill.simple_name().into()).unwrap();
let num_ty = unifier.get_fresh_var_with_range(
&[int32, int64, float, boolean, uint32, uint64],
@ -483,14 +464,14 @@ impl<'a> BuiltinBuilder<'a> {
PrimDef::Exception => self.build_exception_class_related(prim),
PrimDef::Option
| PrimDef::FunOptionIsSome
| PrimDef::FunOptionIsNone
| PrimDef::FunOptionUnwrap
| PrimDef::OptionIsSome
| PrimDef::OptionIsNone
| PrimDef::OptionUnwrap
| PrimDef::FunSome => self.build_option_class_related(prim),
PrimDef::List => self.build_list_class_related(prim),
PrimDef::NDArray | PrimDef::FunNDArrayCopy | PrimDef::FunNDArrayFill => {
PrimDef::NDArray | PrimDef::NDArrayCopy | PrimDef::NDArrayFill => {
self.build_ndarray_class_related(prim)
}
@ -575,22 +556,6 @@ impl<'a> BuiltinBuilder<'a> {
| PrimDef::FunNpLdExp
| PrimDef::FunNpHypot
| PrimDef::FunNpNextAfter => self.build_np_2ary_function(prim),
PrimDef::FunNpTranspose | PrimDef::FunNpReshape => {
self.build_np_sp_ndarray_function(prim)
}
PrimDef::FunNpDot
| PrimDef::FunNpLinalgCholesky
| PrimDef::FunNpLinalgQr
| PrimDef::FunNpLinalgSvd
| PrimDef::FunNpLinalgInv
| PrimDef::FunNpLinalgPinv
| PrimDef::FunNpLinalgMatrixPower
| PrimDef::FunNpLinalgDet
| PrimDef::FunSpLinalgLu
| PrimDef::FunSpLinalgSchur
| PrimDef::FunSpLinalgHessenberg => self.build_linalg_methods(prim),
};
if cfg!(debug_assertions) {
@ -648,24 +613,17 @@ impl<'a> BuiltinBuilder<'a> {
let make_ctor_signature = |unifier: &mut Unifier| {
unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![
FuncArg {
name: "start".into(),
ty: int32,
default_value: None,
is_vararg: false,
},
FuncArg { name: "start".into(), ty: int32, default_value: None },
FuncArg {
name: "stop".into(),
ty: int32,
// placeholder
default_value: Some(SymbolValue::I32(0)),
is_vararg: false,
},
FuncArg {
name: "step".into(),
ty: int32,
default_value: Some(SymbolValue::I32(1)),
is_vararg: false,
},
],
ret: range,
@ -836,9 +794,9 @@ impl<'a> BuiltinBuilder<'a> {
prim,
&[
PrimDef::Option,
PrimDef::FunOptionIsSome,
PrimDef::FunOptionIsNone,
PrimDef::FunOptionUnwrap,
PrimDef::OptionIsSome,
PrimDef::OptionIsNone,
PrimDef::OptionUnwrap,
PrimDef::FunSome,
],
);
@ -851,9 +809,9 @@ impl<'a> BuiltinBuilder<'a> {
fields: Vec::default(),
attributes: Vec::default(),
methods: vec![
Self::create_method(PrimDef::FunOptionIsSome, self.is_some_ty.0),
Self::create_method(PrimDef::FunOptionIsNone, self.is_some_ty.0),
Self::create_method(PrimDef::FunOptionUnwrap, self.unwrap_ty.0),
Self::create_method(PrimDef::OptionIsSome, self.is_some_ty.0),
Self::create_method(PrimDef::OptionIsNone, self.is_some_ty.0),
Self::create_method(PrimDef::OptionUnwrap, self.unwrap_ty.0),
],
ancestors: vec![TypeAnnotation::CustomClass {
id: prim.id(),
@ -864,7 +822,7 @@ impl<'a> BuiltinBuilder<'a> {
loc: None,
},
PrimDef::FunOptionUnwrap => TopLevelDef::Function {
PrimDef::OptionUnwrap => TopLevelDef::Function {
name: prim.name().into(),
simple_name: prim.simple_name().into(),
signature: self.unwrap_ty.0,
@ -878,7 +836,7 @@ impl<'a> BuiltinBuilder<'a> {
loc: None,
},
PrimDef::FunOptionIsNone | PrimDef::FunOptionIsSome => TopLevelDef::Function {
PrimDef::OptionIsNone | PrimDef::OptionIsSome => TopLevelDef::Function {
name: prim.name().to_string(),
simple_name: prim.simple_name().into(),
signature: self.is_some_ty.0,
@ -899,10 +857,10 @@ impl<'a> BuiltinBuilder<'a> {
};
let returned_int = match prim {
PrimDef::FunOptionIsNone => {
PrimDef::OptionIsNone => {
ctx.builder.build_is_null(ptr, prim.simple_name())
}
PrimDef::FunOptionIsSome => {
PrimDef::OptionIsSome => {
ctx.builder.build_is_not_null(ptr, prim.simple_name())
}
_ => unreachable!(),
@ -921,7 +879,6 @@ impl<'a> BuiltinBuilder<'a> {
name: "n".into(),
ty: self.option_tvar.ty,
default_value: None,
is_vararg: false,
}],
ret: self.primitives.option,
vars: into_var_map([self.option_tvar]),
@ -976,7 +933,7 @@ impl<'a> BuiltinBuilder<'a> {
fn build_ndarray_class_related(&self, prim: PrimDef) -> TopLevelDef {
debug_assert_prim_is_allowed(
prim,
&[PrimDef::NDArray, PrimDef::FunNDArrayCopy, PrimDef::FunNDArrayFill],
&[PrimDef::NDArray, PrimDef::NDArrayCopy, PrimDef::NDArrayFill],
);
match prim {
@ -987,8 +944,8 @@ impl<'a> BuiltinBuilder<'a> {
fields: Vec::default(),
attributes: Vec::default(),
methods: vec![
Self::create_method(PrimDef::FunNDArrayCopy, self.ndarray_copy_ty.0),
Self::create_method(PrimDef::FunNDArrayFill, self.ndarray_fill_ty.0),
Self::create_method(PrimDef::NDArrayCopy, self.ndarray_copy_ty.0),
Self::create_method(PrimDef::NDArrayFill, self.ndarray_fill_ty.0),
],
ancestors: Vec::default(),
constructor: None,
@ -996,7 +953,7 @@ impl<'a> BuiltinBuilder<'a> {
loc: None,
},
PrimDef::FunNDArrayCopy => TopLevelDef::Function {
PrimDef::NDArrayCopy => TopLevelDef::Function {
name: prim.name().into(),
simple_name: prim.simple_name().into(),
signature: self.ndarray_copy_ty.0,
@ -1013,7 +970,7 @@ impl<'a> BuiltinBuilder<'a> {
loc: None,
},
PrimDef::FunNDArrayFill => TopLevelDef::Function {
PrimDef::NDArrayFill => TopLevelDef::Function {
name: prim.name().into(),
simple_name: prim.simple_name().into(),
signature: self.ndarray_fill_ty.0,
@ -1056,7 +1013,6 @@ impl<'a> BuiltinBuilder<'a> {
name: "n".into(),
ty: self.num_or_ndarray_ty.ty,
default_value: None,
is_vararg: false,
}],
ret: self.num_or_ndarray_ty.ty,
vars: self.num_or_ndarray_var_map.clone(),
@ -1276,23 +1232,16 @@ impl<'a> BuiltinBuilder<'a> {
simple_name: prim.simple_name().into(),
signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![
FuncArg {
name: "object".into(),
ty: tv.ty,
default_value: None,
is_vararg: false,
},
FuncArg { name: "object".into(), ty: tv.ty, default_value: None },
FuncArg {
name: "copy".into(),
ty: bool,
default_value: Some(SymbolValue::Bool(true)),
is_vararg: false,
},
FuncArg {
name: "ndmin".into(),
ty: int32,
default_value: Some(SymbolValue::U32(0)),
is_vararg: false,
},
],
ret: ndarray,
@ -1334,24 +1283,17 @@ impl<'a> BuiltinBuilder<'a> {
simple_name: prim.simple_name().into(),
signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![
FuncArg {
name: "N".into(),
ty: int32,
default_value: None,
is_vararg: false,
},
FuncArg { name: "N".into(), ty: int32, default_value: None },
// TODO(Derppening): Default values current do not work?
FuncArg {
name: "M".into(),
ty: int32,
default_value: Some(SymbolValue::OptionNone),
is_vararg: false,
},
FuncArg {
name: "k".into(),
ty: int32,
default_value: Some(SymbolValue::I32(0)),
is_vararg: false,
},
],
ret: self.ndarray_float_2d,
@ -1395,12 +1337,7 @@ impl<'a> BuiltinBuilder<'a> {
name: prim.name().into(),
simple_name: prim.simple_name().into(),
signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![FuncArg {
name: "s".into(),
ty: str,
default_value: None,
is_vararg: false,
}],
args: vec![FuncArg { name: "s".into(), ty: str, default_value: None }],
ret: str,
vars: VarMap::default(),
})),
@ -1464,21 +1401,31 @@ impl<'a> BuiltinBuilder<'a> {
fn build_len_function(&mut self) -> TopLevelDef {
let prim = PrimDef::FunLen;
// Type handled in [`Inferencer::try_fold_special_call`]
let arg_tvar = self.unifier.get_dummy_var();
let PrimitiveStore { uint64, int32, .. } = *self.primitives;
let tvar = self.unifier.get_fresh_var(Some("L".into()), None);
let list = self
.unifier
.subst(
self.primitives.list,
&into_var_map([TypeVar { id: self.list_tvar.id, ty: tvar.ty }]),
)
.unwrap();
let ndims = self.unifier.get_fresh_const_generic_var(uint64, Some("N".into()), None);
let ndarray = make_ndarray_ty(self.unifier, self.primitives, Some(tvar.ty), Some(ndims.ty));
let arg_ty = self.unifier.get_fresh_var_with_range(
&[list, ndarray, self.primitives.range],
Some("I".into()),
None,
);
TopLevelDef::Function {
name: prim.name().into(),
simple_name: prim.simple_name().into(),
signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![FuncArg {
name: "obj".into(),
ty: arg_tvar.ty,
default_value: None,
is_vararg: false,
}],
ret: self.primitives.int32,
vars: into_var_map([arg_tvar]),
args: vec![FuncArg { name: "ls".into(), ty: arg_ty.ty, default_value: None }],
ret: int32,
vars: into_var_map([tvar, arg_ty]),
})),
var_id: Vec::default(),
instance_to_symbol: HashMap::default(),
@ -1486,10 +1433,86 @@ impl<'a> BuiltinBuilder<'a> {
resolver: None,
codegen_callback: Some(Arc::new(GenCall::new(Box::new(
move |ctx, _, fun, args, generator| {
let range_ty = ctx.primitives.range;
let arg_ty = fun.0.args[0].ty;
let arg = args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
Ok(if ctx.unifier.unioned(arg_ty, range_ty) {
let arg = RangeValue::from_ptr_val(arg.into_pointer_value(), Some("range"));
let (start, end, step) = destructure_range(ctx, arg);
Some(calculate_len_for_slice_range(generator, ctx, start, end, step).into())
} else {
match &*ctx.unifier.get_ty_immutable(arg_ty) {
TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::List.id() => {
let int32 = ctx.ctx.i32_type();
let zero = int32.const_zero();
let len = ctx
.build_gep_and_load(
arg.into_pointer_value(),
&[zero, int32.const_int(1, false)],
None,
)
.into_int_value();
if len.get_type().get_bit_width() == 32 {
Some(len.into())
} else {
Some(
ctx.builder
.build_int_truncate(len, int32, "len2i32")
.map(Into::into)
.unwrap(),
)
}
}
TypeEnum::TObj { obj_id, .. } if *obj_id == PrimDef::NDArray.id() => {
let llvm_i32 = ctx.ctx.i32_type();
let llvm_usize = generator.get_size_type(ctx.ctx);
builtin_fns::call_len(generator, ctx, (arg_ty, arg)).map(|ret| Some(ret.into()))
let arg = NDArrayValue::from_ptr_val(
arg.into_pointer_value(),
llvm_usize,
None,
);
let ndims = arg.dim_sizes().size(ctx, generator);
ctx.make_assert(
generator,
ctx.builder
.build_int_compare(
IntPredicate::NE,
ndims,
llvm_usize.const_zero(),
"",
)
.unwrap(),
"0:TypeError",
&format!("{name}() of unsized object", name = prim.name()),
[None, None, None],
ctx.current_loc,
);
let len = unsafe {
arg.dim_sizes().get_typed_unchecked(
ctx,
generator,
&llvm_usize.const_zero(),
None,
)
};
if len.get_type().get_bit_width() == 32 {
Some(len.into())
} else {
Some(
ctx.builder
.build_int_truncate(len, llvm_i32, "len")
.map(Into::into)
.unwrap(),
)
}
}
_ => unreachable!(),
}
})
},
)))),
loc: None,
@ -1505,18 +1528,8 @@ impl<'a> BuiltinBuilder<'a> {
simple_name: prim.simple_name().into(),
signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![
FuncArg {
name: "m".into(),
ty: self.num_ty.ty,
default_value: None,
is_vararg: false,
},
FuncArg {
name: "n".into(),
ty: self.num_ty.ty,
default_value: None,
is_vararg: false,
},
FuncArg { name: "m".into(), ty: self.num_ty.ty, default_value: None },
FuncArg { name: "n".into(), ty: self.num_ty.ty, default_value: None },
],
ret: self.num_ty.ty,
vars: self.num_var_map.clone(),
@ -1598,12 +1611,7 @@ impl<'a> BuiltinBuilder<'a> {
signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: param_ty
.iter()
.map(|p| FuncArg {
name: p.1.into(),
ty: p.0,
default_value: None,
is_vararg: false,
})
.map(|p| FuncArg { name: p.1.into(), ty: p.0, default_value: None })
.collect(),
ret: ret_ty.ty,
vars: into_var_map([x1_ty, x2_ty, ret_ty]),
@ -1644,7 +1652,6 @@ impl<'a> BuiltinBuilder<'a> {
name: "n".into(),
ty: self.num_or_ndarray_ty.ty,
default_value: None,
is_vararg: false,
}],
ret: self.num_or_ndarray_ty.ty,
vars: self.num_or_ndarray_var_map.clone(),
@ -1833,12 +1840,7 @@ impl<'a> BuiltinBuilder<'a> {
signature: self.unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: param_ty
.iter()
.map(|p| FuncArg {
name: p.1.into(),
ty: p.0,
default_value: None,
is_vararg: false,
})
.map(|p| FuncArg { name: p.1.into(), ty: p.0, default_value: None })
.collect(),
ret: ret_ty.ty,
vars: into_var_map([x1_ty, x2_ty, ret_ty]),
@ -1872,207 +1874,6 @@ impl<'a> BuiltinBuilder<'a> {
}
}
/// Build np/sp functions that take as input `NDArray` only
fn build_np_sp_ndarray_function(&mut self, prim: PrimDef) -> TopLevelDef {
debug_assert_prim_is_allowed(prim, &[PrimDef::FunNpTranspose, PrimDef::FunNpReshape]);
match prim {
PrimDef::FunNpTranspose => {
let ndarray_ty = self.unifier.get_fresh_var_with_range(
&[self.ndarray_num_ty],
Some("T".into()),
None,
);
create_fn_by_codegen(
self.unifier,
&into_var_map([ndarray_ty]),
prim.name(),
ndarray_ty.ty,
&[(ndarray_ty.ty, "x")],
Box::new(move |ctx, _, fun, args, generator| {
let arg_ty = fun.0.args[0].ty;
let arg_val =
args[0].1.clone().to_basic_value_enum(ctx, generator, arg_ty)?;
Ok(Some(ndarray_transpose(generator, ctx, (arg_ty, arg_val))?))
}),
)
}
// NOTE: on `ndarray_factory_fn_shape_arg_tvar` and
// the `param_ty` for `create_fn_by_codegen`.
//
// Similar to `build_ndarray_from_shape_factory_function` we delegate the responsibility of typechecking
// to [`typecheck::type_inferencer::Inferencer::fold_numpy_function_call_shape_argument`],
// and use a dummy [`TypeVar`] `ndarray_factory_fn_shape_arg_tvar` as a placeholder for `param_ty`.
PrimDef::FunNpReshape => create_fn_by_codegen(
self.unifier,
&VarMap::new(),
prim.name(),
self.ndarray_num_ty,
&[(self.ndarray_num_ty, "x"), (self.ndarray_factory_fn_shape_arg_tvar.ty, "shape")],
Box::new(move |ctx, _, fun, args, generator| {
let x1_ty = fun.0.args[0].ty;
let x1_val = args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
let x2_ty = fun.0.args[1].ty;
let x2_val = args[1].1.clone().to_basic_value_enum(ctx, generator, x2_ty)?;
Ok(Some(ndarray_reshape(generator, ctx, (x1_ty, x1_val), (x2_ty, x2_val))?))
}),
),
_ => unreachable!(),
}
}
/// Build `np_linalg` and `sp_linalg` functions
///
/// The input to these functions must be floating point `NDArray`
fn build_linalg_methods(&mut self, prim: PrimDef) -> TopLevelDef {
debug_assert_prim_is_allowed(
prim,
&[
PrimDef::FunNpDot,
PrimDef::FunNpLinalgCholesky,
PrimDef::FunNpLinalgQr,
PrimDef::FunNpLinalgSvd,
PrimDef::FunNpLinalgInv,
PrimDef::FunNpLinalgPinv,
PrimDef::FunNpLinalgMatrixPower,
PrimDef::FunNpLinalgDet,
PrimDef::FunSpLinalgLu,
PrimDef::FunSpLinalgSchur,
PrimDef::FunSpLinalgHessenberg,
],
);
match prim {
PrimDef::FunNpDot => create_fn_by_codegen(
self.unifier,
&self.num_or_ndarray_var_map,
prim.name(),
self.num_ty.ty,
&[(self.num_or_ndarray_ty.ty, "x1"), (self.num_or_ndarray_ty.ty, "x2")],
Box::new(move |ctx, _, fun, args, generator| {
let x1_ty = fun.0.args[0].ty;
let x1_val = args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
let x2_ty = fun.0.args[1].ty;
let x2_val = args[1].1.clone().to_basic_value_enum(ctx, generator, x2_ty)?;
Ok(Some(ndarray_dot(generator, ctx, (x1_ty, x1_val), (x2_ty, x2_val))?))
}),
),
PrimDef::FunNpLinalgCholesky | PrimDef::FunNpLinalgInv | PrimDef::FunNpLinalgPinv => {
create_fn_by_codegen(
self.unifier,
&VarMap::new(),
prim.name(),
self.ndarray_float_2d,
&[(self.ndarray_float_2d, "x1")],
Box::new(move |ctx, _, fun, args, generator| {
let x1_ty = fun.0.args[0].ty;
let x1_val =
args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
let func = match prim {
PrimDef::FunNpLinalgCholesky => builtin_fns::call_np_linalg_cholesky,
PrimDef::FunNpLinalgInv => builtin_fns::call_np_linalg_inv,
PrimDef::FunNpLinalgPinv => builtin_fns::call_np_linalg_pinv,
_ => unreachable!(),
};
Ok(Some(func(generator, ctx, (x1_ty, x1_val))?))
}),
)
}
PrimDef::FunNpLinalgQr
| PrimDef::FunSpLinalgLu
| PrimDef::FunSpLinalgSchur
| PrimDef::FunSpLinalgHessenberg => {
let ret_ty = self.unifier.add_ty(TypeEnum::TTuple {
ty: vec![self.ndarray_float_2d, self.ndarray_float_2d],
is_vararg_ctx: false,
});
create_fn_by_codegen(
self.unifier,
&VarMap::new(),
prim.name(),
ret_ty,
&[(self.ndarray_float_2d, "x1")],
Box::new(move |ctx, _, fun, args, generator| {
let x1_ty = fun.0.args[0].ty;
let x1_val =
args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
let func = match prim {
PrimDef::FunNpLinalgQr => builtin_fns::call_np_linalg_qr,
PrimDef::FunSpLinalgLu => builtin_fns::call_sp_linalg_lu,
PrimDef::FunSpLinalgSchur => builtin_fns::call_sp_linalg_schur,
PrimDef::FunSpLinalgHessenberg => {
builtin_fns::call_sp_linalg_hessenberg
}
_ => unreachable!(),
};
Ok(Some(func(generator, ctx, (x1_ty, x1_val))?))
}),
)
}
PrimDef::FunNpLinalgSvd => {
let ret_ty = self.unifier.add_ty(TypeEnum::TTuple {
ty: vec![self.ndarray_float_2d, self.ndarray_float, self.ndarray_float_2d],
is_vararg_ctx: false,
});
create_fn_by_codegen(
self.unifier,
&VarMap::new(),
prim.name(),
ret_ty,
&[(self.ndarray_float_2d, "x1")],
Box::new(move |ctx, _, fun, args, generator| {
let x1_ty = fun.0.args[0].ty;
let x1_val =
args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
Ok(Some(builtin_fns::call_np_linalg_svd(generator, ctx, (x1_ty, x1_val))?))
}),
)
}
PrimDef::FunNpLinalgMatrixPower => create_fn_by_codegen(
self.unifier,
&VarMap::new(),
prim.name(),
self.ndarray_float_2d,
&[(self.ndarray_float_2d, "x1"), (self.primitives.int32, "power")],
Box::new(move |ctx, _, fun, args, generator| {
let x1_ty = fun.0.args[0].ty;
let x1_val = args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
let x2_ty = fun.0.args[1].ty;
let x2_val = args[1].1.clone().to_basic_value_enum(ctx, generator, x2_ty)?;
Ok(Some(builtin_fns::call_np_linalg_matrix_power(
generator,
ctx,
(x1_ty, x1_val),
(x2_ty, x2_val),
)?))
}),
),
PrimDef::FunNpLinalgDet => create_fn_by_codegen(
self.unifier,
&VarMap::new(),
prim.name(),
self.primitives.float,
&[(self.ndarray_float_2d, "x1")],
Box::new(move |ctx, _, fun, args, generator| {
let x1_ty = fun.0.args[0].ty;
let x1_val = args[0].1.clone().to_basic_value_enum(ctx, generator, x1_ty)?;
Ok(Some(builtin_fns::call_np_linalg_det(generator, ctx, (x1_ty, x1_val))?))
}),
),
_ => unreachable!(),
}
}
fn create_method(prim: PrimDef, method_ty: Type) -> (StrRef, Type, DefinitionId) {
(prim.simple_name().into(), method_ty, prim.id())
}

View File

@ -44,27 +44,12 @@ pub struct TopLevelComposer {
pub size_t: u32,
}
/// The specification for a builtin function, consisting of the function name, the function
/// signature, and a [code generation callback][`GenCall`].
pub type BuiltinFuncSpec = (StrRef, FunSignature, Arc<GenCall>);
/// A function that creates a [`BuiltinFuncSpec`] using the provided [`PrimitiveStore`] and
/// [`Unifier`].
pub type BuiltinFuncCreator = dyn Fn(&PrimitiveStore, &mut Unifier) -> BuiltinFuncSpec;
impl TopLevelComposer {
/// return a composer and things to make a "primitive" symbol resolver, so that the symbol
/// resolver can later figure out primitive tye definitions when passed a primitive type name
///
/// `lateinit_builtins` are specifically for the ARTIQ module. Since the [`Unifier`] instance
/// used to create builtin functions do not persist until method compilation, any types
/// created (e.g. [`TypeEnum::TVar`]) also do not persist. Those functions should be instead put
/// in `lateinit_builtins`, where they will be instantiated with the [`Unifier`] instance used
/// for method compilation.
/// resolver can later figure out primitive type definitions when passed a primitive type name
#[must_use]
pub fn new(
builtins: Vec<BuiltinFuncSpec>,
lateinit_builtins: Vec<Box<BuiltinFuncCreator>>,
builtins: Vec<(StrRef, FunSignature, Arc<GenCall>)>,
core_config: ComposerConfig,
size_t: u32,
) -> (Self, HashMap<StrRef, DefinitionId>, HashMap<StrRef, Type>) {
@ -134,13 +119,7 @@ impl TopLevelComposer {
}
}
// Materialize lateinit_builtins, now that the unifier is ready
let lateinit_builtins = lateinit_builtins
.into_iter()
.map(|builtin| builtin(&primitives_ty, &mut unifier))
.collect_vec();
for (name, sig, codegen_callback) in builtins.into_iter().chain(lateinit_builtins) {
for (name, sig, codegen_callback) in builtins {
let fun_sig = unifier.add_ty(TypeEnum::TFunc(sig));
builtin_ty.insert(name, fun_sig);
builtin_id.insert(name, DefinitionId(definition_ast_list.len()));
@ -881,73 +860,7 @@ impl TopLevelComposer {
let resolver = &**resolver;
let mut function_var_map = VarMap::new();
let vararg = args
.vararg
.as_ref()
.map(|vararg| -> Result<_, HashSet<String>> {
let vararg = vararg.as_ref();
let annotation = vararg
.node
.annotation
.as_ref()
.ok_or_else(|| {
HashSet::from([format!(
"function parameter `{}` needs type annotation at {}",
vararg.node.arg, vararg.location
)])
})?
.as_ref();
let type_annotation = parse_ast_to_type_annotation_kinds(
resolver,
temp_def_list.as_slice(),
unifier,
primitives_store,
annotation,
// NOTE: since only class need this, for function
// it should be fine to be empty map
HashMap::new(),
)?;
let type_vars_within =
get_type_var_contained_in_type_annotation(&type_annotation)
.into_iter()
.map(|x| -> Result<TypeVar, HashSet<String>> {
let TypeAnnotation::TypeVar(ty) = x else {
unreachable!("must be type var annotation kind")
};
let id = Self::get_var_id(ty, unifier)?;
Ok(TypeVar { id, ty })
})
.collect::<Result<Vec<_>, _>>()?;
for var in type_vars_within {
if let Some(prev_ty) = function_var_map.insert(var.id, var.ty) {
// if already have the type inserted, make sure they are the same thing
assert_eq!(prev_ty, var.ty);
}
}
let ty = get_type_from_type_annotation_kinds(
temp_def_list.as_ref(),
unifier,
primitives_store,
&type_annotation,
&mut None,
)?;
Ok(FuncArg {
name: vararg.node.arg,
ty,
default_value: Some(SymbolValue::Tuple(Vec::default())),
is_vararg: true,
})
})
.transpose()?;
let mut arg_types = {
let arg_types = {
// make sure no duplicate parameter
let mut defined_parameter_name: HashSet<_> = HashSet::new();
for x in &args.args {
@ -1048,18 +961,11 @@ impl TopLevelComposer {
v
}),
},
is_vararg: false,
})
})
.collect::<Result<Vec<_>, _>>()?
};
if let Some(vararg) = vararg {
arg_types.push(vararg);
};
let arg_types = arg_types;
let return_ty = {
if let Some(returns) = returns {
let return_ty_annotation = {
@ -1311,7 +1217,6 @@ impl TopLevelComposer {
})
}
},
is_vararg: false,
};
// push the dummy type and the type annotation
// into the list for later unification
@ -1737,25 +1642,21 @@ impl TopLevelComposer {
name: "msg".into(),
ty: string,
default_value: Some(SymbolValue::Str(String::new())),
is_vararg: false,
},
FuncArg {
name: "param0".into(),
ty: int64,
default_value: Some(SymbolValue::I64(0)),
is_vararg: false,
},
FuncArg {
name: "param1".into(),
ty: int64,
default_value: Some(SymbolValue::I64(0)),
is_vararg: false,
},
FuncArg {
name: "param2".into(),
ty: int64,
default_value: Some(SymbolValue::I64(0)),
is_vararg: false,
},
],
ret: self_type,
@ -1822,12 +1723,13 @@ impl TopLevelComposer {
if *name != init_str_id {
unreachable!("must be init function here")
}
// let all_inited = Self::get_all_assigned_field(body.as_slice())?;
let all_inited = Self::get_all_assigned_field(
object_id.0,
definition_ast_list,
def,
body.as_slice(),
)?;
for (f, _, _) in fields {
if !all_inited.contains(f) {
return Err(HashSet::from([
@ -1970,7 +1872,6 @@ impl TopLevelComposer {
name: a.name,
ty: unifier.subst(a.ty, &subst).unwrap_or(a.ty),
default_value: a.default_value.clone(),
is_vararg: false,
})
.collect_vec()
};

View File

@ -28,22 +28,17 @@ pub enum PrimDef {
List,
NDArray,
// Option methods
FunOptionIsSome,
FunOptionIsNone,
FunOptionUnwrap,
// Option-related functions
FunSome,
// NDArray methods
FunNDArrayCopy,
FunNDArrayFill,
// Range methods
FunRangeInit,
// NumPy factory functions
// Member Functions
OptionIsSome,
OptionIsNone,
OptionUnwrap,
NDArrayCopy,
NDArrayFill,
FunInt32,
FunInt64,
FunUInt32,
FunUInt64,
FunFloat,
FunNpNDArray,
FunNpEmpty,
FunNpZeros,
@ -52,17 +47,28 @@ pub enum PrimDef {
FunNpArray,
FunNpEye,
FunNpIdentity,
// Miscellaneous NumPy & SciPy functions
FunRound,
FunRound64,
FunNpRound,
FunRangeInit,
FunStr,
FunBool,
FunFloor,
FunFloor64,
FunNpFloor,
FunCeil,
FunCeil64,
FunNpCeil,
FunLen,
FunMin,
FunNpMin,
FunNpMinimum,
FunNpArgmin,
FunMax,
FunNpMax,
FunNpMaximum,
FunNpArgmax,
FunAbs,
FunNpIsNan,
FunNpIsInf,
FunNpSin,
@ -100,40 +106,9 @@ pub enum PrimDef {
FunNpLdExp,
FunNpHypot,
FunNpNextAfter,
FunNpTranspose,
FunNpReshape,
// Linalg functions
FunNpDot,
FunNpLinalgCholesky,
FunNpLinalgQr,
FunNpLinalgSvd,
FunNpLinalgInv,
FunNpLinalgPinv,
FunNpLinalgMatrixPower,
FunNpLinalgDet,
FunSpLinalgLu,
FunSpLinalgSchur,
FunSpLinalgHessenberg,
// Miscellaneous Python & NAC3 functions
FunInt32,
FunInt64,
FunUInt32,
FunUInt64,
FunFloat,
FunRound,
FunRound64,
FunStr,
FunBool,
FunFloor,
FunFloor64,
FunCeil,
FunCeil64,
FunLen,
FunMin,
FunMax,
FunAbs,
// Top-Level Functions
FunSome,
}
/// Associated details of a [`PrimDef`]
@ -199,7 +174,6 @@ impl PrimDef {
}
match self {
// Classes
PrimDef::Int32 => class("int32", |primitives| primitives.int32),
PrimDef::Int64 => class("int64", |primitives| primitives.int64),
PrimDef::Float => class("float", |primitives| primitives.float),
@ -211,25 +185,18 @@ impl PrimDef {
PrimDef::UInt32 => class("uint32", |primitives| primitives.uint32),
PrimDef::UInt64 => class("uint64", |primitives| primitives.uint64),
PrimDef::Option => class("Option", |primitives| primitives.option),
PrimDef::OptionIsSome => fun("Option.is_some", Some("is_some")),
PrimDef::OptionIsNone => fun("Option.is_none", Some("is_none")),
PrimDef::OptionUnwrap => fun("Option.unwrap", Some("unwrap")),
PrimDef::List => class("list", |primitives| primitives.list),
PrimDef::NDArray => class("ndarray", |primitives| primitives.ndarray),
// Option methods
PrimDef::FunOptionIsSome => fun("Option.is_some", Some("is_some")),
PrimDef::FunOptionIsNone => fun("Option.is_none", Some("is_none")),
PrimDef::FunOptionUnwrap => fun("Option.unwrap", Some("unwrap")),
// Option-related functions
PrimDef::FunSome => fun("Some", None),
// NDArray methods
PrimDef::FunNDArrayCopy => fun("ndarray.copy", Some("copy")),
PrimDef::FunNDArrayFill => fun("ndarray.fill", Some("fill")),
// Range methods
PrimDef::FunRangeInit => fun("range.__init__", Some("__init__")),
// NumPy factory functions
PrimDef::NDArrayCopy => fun("ndarray.copy", Some("copy")),
PrimDef::NDArrayFill => fun("ndarray.fill", Some("fill")),
PrimDef::FunInt32 => fun("int32", None),
PrimDef::FunInt64 => fun("int64", None),
PrimDef::FunUInt32 => fun("uint32", None),
PrimDef::FunUInt64 => fun("uint64", None),
PrimDef::FunFloat => fun("float", None),
PrimDef::FunNpNDArray => fun("np_ndarray", None),
PrimDef::FunNpEmpty => fun("np_empty", None),
PrimDef::FunNpZeros => fun("np_zeros", None),
@ -238,17 +205,28 @@ impl PrimDef {
PrimDef::FunNpArray => fun("np_array", None),
PrimDef::FunNpEye => fun("np_eye", None),
PrimDef::FunNpIdentity => fun("np_identity", None),
// Miscellaneous NumPy & SciPy functions
PrimDef::FunRound => fun("round", None),
PrimDef::FunRound64 => fun("round64", None),
PrimDef::FunNpRound => fun("np_round", None),
PrimDef::FunRangeInit => fun("range.__init__", Some("__init__")),
PrimDef::FunStr => fun("str", None),
PrimDef::FunBool => fun("bool", None),
PrimDef::FunFloor => fun("floor", None),
PrimDef::FunFloor64 => fun("floor64", None),
PrimDef::FunNpFloor => fun("np_floor", None),
PrimDef::FunCeil => fun("ceil", None),
PrimDef::FunCeil64 => fun("ceil64", None),
PrimDef::FunNpCeil => fun("np_ceil", None),
PrimDef::FunLen => fun("len", None),
PrimDef::FunMin => fun("min", None),
PrimDef::FunNpMin => fun("np_min", None),
PrimDef::FunNpMinimum => fun("np_minimum", None),
PrimDef::FunNpArgmin => fun("np_argmin", None),
PrimDef::FunMax => fun("max", None),
PrimDef::FunNpMax => fun("np_max", None),
PrimDef::FunNpMaximum => fun("np_maximum", None),
PrimDef::FunNpArgmax => fun("np_argmax", None),
PrimDef::FunAbs => fun("abs", None),
PrimDef::FunNpIsNan => fun("np_isnan", None),
PrimDef::FunNpIsInf => fun("np_isinf", None),
PrimDef::FunNpSin => fun("np_sin", None),
@ -286,40 +264,7 @@ impl PrimDef {
PrimDef::FunNpLdExp => fun("np_ldexp", None),
PrimDef::FunNpHypot => fun("np_hypot", None),
PrimDef::FunNpNextAfter => fun("np_nextafter", None),
PrimDef::FunNpTranspose => fun("np_transpose", None),
PrimDef::FunNpReshape => fun("np_reshape", None),
// Linalg functions
PrimDef::FunNpDot => fun("np_dot", None),
PrimDef::FunNpLinalgCholesky => fun("np_linalg_cholesky", None),
PrimDef::FunNpLinalgQr => fun("np_linalg_qr", None),
PrimDef::FunNpLinalgSvd => fun("np_linalg_svd", None),
PrimDef::FunNpLinalgInv => fun("np_linalg_inv", None),
PrimDef::FunNpLinalgPinv => fun("np_linalg_pinv", None),
PrimDef::FunNpLinalgMatrixPower => fun("np_linalg_matrix_power", None),
PrimDef::FunNpLinalgDet => fun("np_linalg_det", None),
PrimDef::FunSpLinalgLu => fun("sp_linalg_lu", None),
PrimDef::FunSpLinalgSchur => fun("sp_linalg_schur", None),
PrimDef::FunSpLinalgHessenberg => fun("sp_linalg_hessenberg", None),
// Miscellaneous Python & NAC3 functions
PrimDef::FunInt32 => fun("int32", None),
PrimDef::FunInt64 => fun("int64", None),
PrimDef::FunUInt32 => fun("uint32", None),
PrimDef::FunUInt64 => fun("uint64", None),
PrimDef::FunFloat => fun("float", None),
PrimDef::FunRound => fun("round", None),
PrimDef::FunRound64 => fun("round64", None),
PrimDef::FunStr => fun("str", None),
PrimDef::FunBool => fun("bool", None),
PrimDef::FunFloor => fun("floor", None),
PrimDef::FunFloor64 => fun("floor64", None),
PrimDef::FunCeil => fun("ceil", None),
PrimDef::FunCeil64 => fun("ceil64", None),
PrimDef::FunLen => fun("len", None),
PrimDef::FunMin => fun("min", None),
PrimDef::FunMax => fun("max", None),
PrimDef::FunAbs => fun("abs", None),
PrimDef::FunSome => fun("Some", None),
}
}
}
@ -470,9 +415,9 @@ impl TopLevelComposer {
let option = unifier.add_ty(TypeEnum::TObj {
obj_id: PrimDef::Option.id(),
fields: vec![
(PrimDef::FunOptionIsSome.simple_name().into(), (is_some_type_fun_ty, true)),
(PrimDef::FunOptionIsNone.simple_name().into(), (is_some_type_fun_ty, true)),
(PrimDef::FunOptionUnwrap.simple_name().into(), (unwrap_fun_ty, true)),
(PrimDef::OptionIsSome.simple_name().into(), (is_some_type_fun_ty, true)),
(PrimDef::OptionIsNone.simple_name().into(), (is_some_type_fun_ty, true)),
(PrimDef::OptionUnwrap.simple_name().into(), (unwrap_fun_ty, true)),
]
.into_iter()
.collect::<HashMap<_, _>>(),
@ -506,7 +451,6 @@ impl TopLevelComposer {
name: "value".into(),
ty: ndarray_dtype_tvar.ty,
default_value: None,
is_vararg: false,
}],
ret: none,
vars: into_var_map([ndarray_dtype_tvar, ndarray_ndims_tvar]),
@ -514,8 +458,8 @@ impl TopLevelComposer {
let ndarray = unifier.add_ty(TypeEnum::TObj {
obj_id: PrimDef::NDArray.id(),
fields: Mapping::from([
(PrimDef::FunNDArrayCopy.simple_name().into(), (ndarray_copy_fun_ty, true)),
(PrimDef::FunNDArrayFill.simple_name().into(), (ndarray_fill_fun_ty, true)),
(PrimDef::NDArrayCopy.simple_name().into(), (ndarray_copy_fun_ty, true)),
(PrimDef::NDArrayFill.simple_name().into(), (ndarray_fill_fun_ty, true)),
]),
params: into_var_map([ndarray_dtype_tvar, ndarray_ndims_tvar]),
});
@ -734,14 +678,9 @@ impl TopLevelComposer {
)
}
/// This function returns the fields that have been initialized in the `__init__` function of a class
/// The function takes as input:
/// * `class_id`: The `object_id` of the class whose function is being evaluated (check `TopLevelDef::Class`)
/// * `definition_ast_list`: A list of ast definitions and statements defined in `TopLevelComposer`
/// * `stmts`: The body of function being parsed. Each statment is analyzed to check varaible initialization statements
pub fn get_all_assigned_field(
class_id: usize,
definition_ast_list: &Vec<DefAst>,
def: &Arc<RwLock<TopLevelDef>>,
stmts: &[Stmt<()>],
) -> Result<HashSet<StrRef>, HashSet<String>> {
let mut result = HashSet::new();
@ -780,139 +719,150 @@ impl TopLevelComposer {
ast::StmtKind::For { body, orelse, .. }
| ast::StmtKind::While { body, orelse, .. } => {
result.extend(Self::get_all_assigned_field(
class_id,
definition_ast_list,
def,
body.as_slice(),
)?);
result.extend(Self::get_all_assigned_field(
class_id,
definition_ast_list,
def,
orelse.as_slice(),
)?);
}
ast::StmtKind::If { body, orelse, .. } => {
let inited_for_sure = Self::get_all_assigned_field(
class_id,
definition_ast_list,
body.as_slice(),
)?
.intersection(&Self::get_all_assigned_field(
class_id,
definition_ast_list,
orelse.as_slice(),
)?)
.copied()
.collect::<HashSet<_>>();
let inited_for_sure =
Self::get_all_assigned_field(definition_ast_list, def, body.as_slice())?
.intersection(&Self::get_all_assigned_field(
definition_ast_list,
def,
orelse.as_slice(),
)?)
.copied()
.collect::<HashSet<_>>();
result.extend(inited_for_sure);
}
ast::StmtKind::Try { body, orelse, finalbody, .. } => {
let inited_for_sure = Self::get_all_assigned_field(
class_id,
definition_ast_list,
body.as_slice(),
)?
.intersection(&Self::get_all_assigned_field(
class_id,
definition_ast_list,
orelse.as_slice(),
)?)
.copied()
.collect::<HashSet<_>>();
let inited_for_sure =
Self::get_all_assigned_field(definition_ast_list, def, body.as_slice())?
.intersection(&Self::get_all_assigned_field(
definition_ast_list,
def,
orelse.as_slice(),
)?)
.copied()
.collect::<HashSet<_>>();
result.extend(inited_for_sure);
result.extend(Self::get_all_assigned_field(
class_id,
definition_ast_list,
def,
finalbody.as_slice(),
)?);
}
ast::StmtKind::With { body, .. } => {
result.extend(Self::get_all_assigned_field(
class_id,
definition_ast_list,
def,
body.as_slice(),
)?);
}
// Variables Initialized in function calls
// If its a call to __init__function of ancestor extend with ancestor fields
ast::StmtKind::Expr { value, .. } => {
let ExprKind::Call { func, .. } = &value.node else {
continue;
};
let ExprKind::Attribute { value, attr, .. } = &func.node else {
continue;
};
let ExprKind::Name { id, .. } = &value.node else {
continue;
};
// Need to consider the two cases:
// Case 1) Call to class function i.e. id = `self`
// Case 2) Call to class ancestor function i.e. id = ancestor_name
// We leave checking whether function in case 2 belonged to class ancestor or not to type checker
//
// According to current handling of `self`, function definition are fixed and do not change regardless
// of which object is passed as `self` i.e. virtual polymorphism is not supported
// Therefore, we change class id for case 2 to reflect behavior of our compiler
// Check if Expression is a function call to self
if let ExprKind::Call { func, args, .. } = &value.node {
if let ExprKind::Attribute { value, attr: fn_name, .. } = &func.node {
let class_def = def.read();
let (ancestors, methods) = {
let mut class_methods: HashMap<StrRef, DefinitionId> =
HashMap::new();
let mut class_ancestors: HashMap<
StrRef,
HashMap<StrRef, DefinitionId>,
> = HashMap::new();
let class_name = if *id == "self".into() {
let ast::StmtKind::ClassDef { name, .. } =
&definition_ast_list[class_id].1.as_ref().unwrap().node
else {
unreachable!()
};
name
} else {
id
};
let parent_method = definition_ast_list.iter().find_map(|def| {
let (
class_def,
Some(ast::Located {
node: ast::StmtKind::ClassDef { name, body, .. },
..
}),
) = &def
else {
return None;
};
let TopLevelDef::Class { object_id: class_id, .. } = &*class_def.read()
else {
unreachable!()
};
if name == class_name {
body.iter().find_map(|m| {
let ast::StmtKind::FunctionDef { name, body, .. } = &m.node else {
return None;
};
if *name == *attr {
return Some((body.clone(), class_id.0));
if let TopLevelDef::Class { methods, ancestors, .. } = &*class_def {
for m in methods {
class_methods.insert(m.0, m.2);
}
ancestors.iter().skip(1).for_each(|a| {
if let TypeAnnotation::CustomClass { id, .. } = a {
let anc_def =
definition_ast_list.get(id.0).unwrap().0.read();
if let TopLevelDef::Class { name, methods, .. } =
&*anc_def
{
let mut temp: HashMap<StrRef, DefinitionId> =
HashMap::new();
for m in methods {
temp.insert(m.0, m.2);
}
// Remove module name suffix from name
let mut name_string = name.to_string();
let split_loc =
name_string.find(|c| c == '.').unwrap() + 1;
class_ancestors.insert(
name_string.split_off(split_loc).into(),
temp,
);
}
}
});
}
None
})
} else {
None
(class_ancestors, class_methods)
};
if let ExprKind::Name { id, .. } = value.node {
if id == "self".into() {
// Get Class methods and fields
let method_id = methods.get(fn_name);
if method_id.is_some() {
if let Some(fn_ast) = &definition_ast_list
.get(method_id.unwrap().0)
.unwrap()
.1
{
if let ast::StmtKind::FunctionDef { body, .. } =
&fn_ast.node
{
result.extend(Self::get_all_assigned_field(
definition_ast_list,
def,
body.as_slice(),
)?);
}
}
}
} else if let Some(ancestor_methods) = ancestors.get(&id) {
// First arg must be `self` when calling ancestor function
if let ExprKind::Name { id, .. } = args[0].node {
if id == "self".into() {
if let Some(method_id) = ancestor_methods.get(fn_name) {
if let Some(fn_ast) =
&definition_ast_list.get(method_id.0).unwrap().1
{
if let ast::StmtKind::FunctionDef {
body, ..
} = &fn_ast.node
{
result.extend(
Self::get_all_assigned_field(
definition_ast_list,
def,
body.as_slice(),
)?,
);
}
}
};
}
}
}
}
}
});
// If method body is none then method does not exist
if let Some((method_body, class_id)) = parent_method {
result.extend(Self::get_all_assigned_field(
class_id,
definition_ast_list,
method_body.as_slice(),
)?);
} else {
return Err(HashSet::from([format!(
"{}.{} not found in class {class_name} at {}",
*id, *attr, value.location
)]));
}
}
ast::StmtKind::Pass { .. }
| ast::StmtKind::Assert { .. }
| ast::StmtKind::AnnAssign { .. } => {}
ast::StmtKind::Pass { .. } | ast::StmtKind::Assert { .. } => {}
_ => {
println!("{:?}", s.node);
unimplemented!()
}
}

View File

@ -130,14 +130,14 @@ pub enum TopLevelDef {
/// Function instance to symbol mapping
///
/// * Key: String representation of type variable values, sorted by variable ID in ascending
/// order, including type variables associated with the class.
/// order, including type variables associated with the class.
/// * Value: Function symbol name.
instance_to_symbol: HashMap<String, String>,
/// Function instances to annotated AST mapping
///
/// * Key: String representation of type variable values, sorted by variable ID in ascending
/// order, including type variables associated with the class. Excluding rigid type
/// variables.
/// order, including type variables associated with the class. Excluding rigid type
/// variables.
///
/// Rigid type variables that would be substituted when the function is instantiated.
instance_to_stmt: HashMap<String, FunInstance>,

View File

@ -10,9 +10,9 @@ use itertools::Itertools;
/// Creates a `ndarray` [`Type`] with the given type arguments.
///
/// * `dtype` - The element type of the `ndarray`, or [`None`] if the type variable is not
/// specialized.
/// specialized.
/// * `ndims` - The number of dimensions of the `ndarray`, or [`None`] if the type variable is not
/// specialized.
/// specialized.
pub fn make_ndarray_ty(
unifier: &mut Unifier,
primitives: &PrimitiveStore,
@ -25,9 +25,9 @@ pub fn make_ndarray_ty(
/// Substitutes type variables in `ndarray`.
///
/// * `dtype` - The element type of the `ndarray`, or [`None`] if the type variable is not
/// specialized.
/// specialized.
/// * `ndims` - The number of dimensions of the `ndarray`, or [`None`] if the type variable is not
/// specialized.
/// specialized.
pub fn subst_ndarray_tvars(
unifier: &mut Unifier,
ndarray: Type,

View File

@ -5,7 +5,7 @@ expression: res_vec
[
"Class {\nname: \"Generic_A\",\nancestors: [\"Generic_A[V]\", \"B\"],\nfields: [\"aa\", \"a\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"foo\", \"fn[[b:T], none]\"), (\"fun\", \"fn[[a:int32], V]\")],\ntype_vars: [\"V\"]\n}\n",
"Function {\nname: \"Generic_A.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"Generic_A.fun\",\nsig: \"fn[[a:int32], V]\",\nvar_id: [TypeVarId(241)]\n}\n",
"Function {\nname: \"Generic_A.fun\",\nsig: \"fn[[a:int32], V]\",\nvar_id: [TypeVarId(245)]\n}\n",
"Class {\nname: \"B\",\nancestors: [\"B\"],\nfields: [\"aa\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"foo\", \"fn[[b:T], none]\")],\ntype_vars: []\n}\n",
"Function {\nname: \"B.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"B.foo\",\nsig: \"fn[[b:T], none]\",\nvar_id: []\n}\n",

View File

@ -7,7 +7,7 @@ expression: res_vec
"Function {\nname: \"A.__init__\",\nsig: \"fn[[t:T], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"A.fun\",\nsig: \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\",\nvar_id: []\n}\n",
"Function {\nname: \"A.foo\",\nsig: \"fn[[c:C], none]\",\nvar_id: []\n}\n",
"Class {\nname: \"B\",\nancestors: [\"B[typevar230]\", \"A[float]\"],\nfields: [\"a\", \"b\", \"c\", \"d\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\"), (\"foo\", \"fn[[c:C], none]\")],\ntype_vars: [\"typevar230\"]\n}\n",
"Class {\nname: \"B\",\nancestors: [\"B[typevar234]\", \"A[float]\"],\nfields: [\"a\", \"b\", \"c\", \"d\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\"), (\"foo\", \"fn[[c:C], none]\")],\ntype_vars: [\"typevar234\"]\n}\n",
"Function {\nname: \"B.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"B.fun\",\nsig: \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\",\nvar_id: []\n}\n",
"Class {\nname: \"C\",\nancestors: [\"C\", \"B[bool]\", \"A[float]\"],\nfields: [\"a\", \"b\", \"c\", \"d\", \"e\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[a:int32, b:T], list[virtual[B[bool]]]]\"), (\"foo\", \"fn[[c:C], none]\")],\ntype_vars: []\n}\n",

View File

@ -5,8 +5,8 @@ expression: res_vec
[
"Function {\nname: \"foo\",\nsig: \"fn[[a:list[int32], b:tuple[T, float]], A[B, bool]]\",\nvar_id: []\n}\n",
"Class {\nname: \"A\",\nancestors: [\"A[T, V]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[v:V], none]\"), (\"fun\", \"fn[[a:T], V]\")],\ntype_vars: [\"T\", \"V\"]\n}\n",
"Function {\nname: \"A.__init__\",\nsig: \"fn[[v:V], none]\",\nvar_id: [TypeVarId(243)]\n}\n",
"Function {\nname: \"A.fun\",\nsig: \"fn[[a:T], V]\",\nvar_id: [TypeVarId(248)]\n}\n",
"Function {\nname: \"A.__init__\",\nsig: \"fn[[v:V], none]\",\nvar_id: [TypeVarId(247)]\n}\n",
"Function {\nname: \"A.fun\",\nsig: \"fn[[a:T], V]\",\nvar_id: [TypeVarId(252)]\n}\n",
"Function {\nname: \"gfun\",\nsig: \"fn[[a:A[list[float], int32]], none]\",\nvar_id: []\n}\n",
"Class {\nname: \"B\",\nancestors: [\"B\"],\nfields: [],\nmethods: [(\"__init__\", \"fn[[], none]\")],\ntype_vars: []\n}\n",
"Function {\nname: \"B.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",

View File

@ -3,7 +3,7 @@ source: nac3core/src/toplevel/test.rs
expression: res_vec
---
[
"Class {\nname: \"A\",\nancestors: [\"A[typevar229, typevar230]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[a:A[float, bool], b:B], none]\"), (\"fun\", \"fn[[a:A[float, bool]], A[bool, int32]]\")],\ntype_vars: [\"typevar229\", \"typevar230\"]\n}\n",
"Class {\nname: \"A\",\nancestors: [\"A[typevar233, typevar234]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[a:A[float, bool], b:B], none]\"), (\"fun\", \"fn[[a:A[float, bool]], A[bool, int32]]\")],\ntype_vars: [\"typevar233\", \"typevar234\"]\n}\n",
"Function {\nname: \"A.__init__\",\nsig: \"fn[[a:A[float, bool], b:B], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"A.fun\",\nsig: \"fn[[a:A[float, bool]], A[bool, int32]]\",\nvar_id: []\n}\n",
"Class {\nname: \"B\",\nancestors: [\"B\", \"A[int64, bool]\"],\nfields: [\"a\", \"b\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[a:A[float, bool]], A[bool, int32]]\"), (\"foo\", \"fn[[b:B], B]\"), (\"bar\", \"fn[[a:A[list[B], int32]], tuple[A[virtual[A[B, int32]], bool], B]]\")],\ntype_vars: []\n}\n",

View File

@ -6,12 +6,12 @@ expression: res_vec
"Class {\nname: \"A\",\nancestors: [\"A\"],\nfields: [\"a\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[b:B], none]\"), (\"foo\", \"fn[[a:T, b:V], none]\")],\ntype_vars: []\n}\n",
"Function {\nname: \"A.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"A.fun\",\nsig: \"fn[[b:B], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"A.foo\",\nsig: \"fn[[a:T, b:V], none]\",\nvar_id: [TypeVarId(249)]\n}\n",
"Function {\nname: \"A.foo\",\nsig: \"fn[[a:T, b:V], none]\",\nvar_id: [TypeVarId(253)]\n}\n",
"Class {\nname: \"B\",\nancestors: [\"B\", \"C\", \"A\"],\nfields: [\"a\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[b:B], none]\"), (\"foo\", \"fn[[a:T, b:V], none]\")],\ntype_vars: []\n}\n",
"Function {\nname: \"B.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
"Class {\nname: \"C\",\nancestors: [\"C\", \"A\"],\nfields: [\"a\"],\nmethods: [(\"__init__\", \"fn[[], none]\"), (\"fun\", \"fn[[b:B], none]\"), (\"foo\", \"fn[[a:T, b:V], none]\")],\ntype_vars: []\n}\n",
"Function {\nname: \"C.__init__\",\nsig: \"fn[[], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"C.fun\",\nsig: \"fn[[b:B], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"foo\",\nsig: \"fn[[a:A], none]\",\nvar_id: []\n}\n",
"Function {\nname: \"ff\",\nsig: \"fn[[a:T], V]\",\nvar_id: [TypeVarId(257)]\n}\n",
"Function {\nname: \"ff\",\nsig: \"fn[[a:T], V]\",\nvar_id: [TypeVarId(261)]\n}\n",
]

View File

@ -117,8 +117,7 @@ impl SymbolResolver for Resolver {
"register"
)]
fn test_simple_register(source: Vec<&str>) {
let mut composer =
TopLevelComposer::new(Vec::new(), Vec::new(), ComposerConfig::default(), 64).0;
let mut composer = TopLevelComposer::new(Vec::new(), ComposerConfig::default(), 64).0;
for s in source {
let ast = parse_program(s, FileName::default()).unwrap();
@ -138,8 +137,7 @@ fn test_simple_register(source: Vec<&str>) {
"register"
)]
fn test_simple_register_without_constructor(source: &str) {
let mut composer =
TopLevelComposer::new(Vec::new(), Vec::new(), ComposerConfig::default(), 64).0;
let mut composer = TopLevelComposer::new(Vec::new(), ComposerConfig::default(), 64).0;
let ast = parse_program(source, FileName::default()).unwrap();
let ast = ast[0].clone();
composer.register_top_level(ast, None, "", true).unwrap();
@ -173,8 +171,7 @@ fn test_simple_register_without_constructor(source: &str) {
"function compose"
)]
fn test_simple_function_analyze(source: &[&str], tys: &[&str], names: &[&str]) {
let mut composer =
TopLevelComposer::new(Vec::new(), Vec::new(), ComposerConfig::default(), 64).0;
let mut composer = TopLevelComposer::new(Vec::new(), ComposerConfig::default(), 64).0;
let internal_resolver = Arc::new(ResolverInternal {
id_to_def: Mutex::default(),
@ -522,8 +519,7 @@ fn test_simple_function_analyze(source: &[&str], tys: &[&str], names: &[&str]) {
)]
fn test_analyze(source: &[&str], res: &[&str]) {
let print = false;
let mut composer =
TopLevelComposer::new(Vec::new(), Vec::new(), ComposerConfig::default(), 64).0;
let mut composer = TopLevelComposer::new(Vec::new(), ComposerConfig::default(), 64).0;
let internal_resolver = make_internal_resolver_with_tvar(
vec![
@ -700,8 +696,7 @@ fn test_analyze(source: &[&str], res: &[&str]) {
)]
fn test_inference(source: Vec<&str>, res: &[&str]) {
let print = true;
let mut composer =
TopLevelComposer::new(Vec::new(), Vec::new(), ComposerConfig::default(), 64).0;
let mut composer = TopLevelComposer::new(Vec::new(), ComposerConfig::default(), 64).0;
let internal_resolver = make_internal_resolver_with_tvar(
vec![

View File

@ -64,9 +64,9 @@ impl TypeAnnotation {
/// Parses an AST expression `expr` into a [`TypeAnnotation`].
///
/// * `locked` - A [`HashMap`] containing the IDs of known definitions, mapped to a [`Vec`] of all
/// generic variables associated with the definition.
/// generic variables associated with the definition.
/// * `type_var` - The type variable associated with the type argument currently being parsed. Pass
/// [`None`] when this function is invoked externally.
/// [`None`] when this function is invoked externally.
pub fn parse_ast_to_type_annotation_kinds<T, S: std::hash::BuildHasher + Clone>(
resolver: &(dyn SymbolResolver + Send + Sync),
top_level_defs: &[Arc<RwLock<TopLevelDef>>],
@ -552,7 +552,7 @@ pub fn get_type_from_type_annotation_kinds(
)
})
.collect::<Result<Vec<_>, _>>()?;
Ok(unifier.add_ty(TypeEnum::TTuple { ty: tys, is_vararg_ctx: false }))
Ok(unifier.add_ty(TypeEnum::TTuple { ty: tys }))
}
}
}

View File

@ -34,18 +34,13 @@ impl<'a> Inferencer<'a> {
self.should_have_value(pattern)?;
Ok(())
}
ExprKind::List { elts, .. } | ExprKind::Tuple { elts, .. } => {
ExprKind::Tuple { elts, .. } => {
for elt in elts {
self.check_pattern(elt, defined_identifiers)?;
self.should_have_value(elt)?;
}
Ok(())
}
ExprKind::Starred { value, .. } => {
self.check_pattern(value, defined_identifiers)?;
self.should_have_value(value)?;
Ok(())
}
ExprKind::Subscript { value, slice, .. } => {
self.check_expr(value, defined_identifiers)?;
self.should_have_value(value)?;
@ -212,23 +207,19 @@ impl<'a> Inferencer<'a> {
/// This is a workaround preventing the caller from using a variable `alloca`-ed in the body, which
/// is freed when the function returns.
fn check_return_value_ty(&mut self, ret_ty: Type) -> bool {
if cfg!(feature = "no-escape-analysis") {
true
} else {
match &*self.unifier.get_ty_immutable(ret_ty) {
TypeEnum::TObj { .. } => [
self.primitives.int32,
self.primitives.int64,
self.primitives.uint32,
self.primitives.uint64,
self.primitives.float,
self.primitives.bool,
]
.iter()
.any(|allowed_ty| self.unifier.unioned(ret_ty, *allowed_ty)),
TypeEnum::TTuple { ty, .. } => ty.iter().all(|t| self.check_return_value_ty(*t)),
_ => false,
}
match &*self.unifier.get_ty_immutable(ret_ty) {
TypeEnum::TObj { .. } => [
self.primitives.int32,
self.primitives.int64,
self.primitives.uint32,
self.primitives.uint64,
self.primitives.float,
self.primitives.bool,
]
.iter()
.any(|allowed_ty| self.unifier.unioned(ret_ty, *allowed_ty)),
TypeEnum::TTuple { ty } => ty.iter().all(|t| self.check_return_value_ty(*t)),
_ => false,
}
}

View File

@ -197,7 +197,6 @@ pub fn impl_binop(
ty: other_ty,
default_value: None,
name: "other".into(),
is_vararg: false,
}],
})),
false,
@ -262,7 +261,6 @@ pub fn impl_cmpop(
ty: other_ty,
default_value: None,
name: "other".into(),
is_vararg: false,
}],
})),
false,
@ -520,23 +518,6 @@ pub fn typeof_binop(
}
Operator::MatMult => {
// NOTE: NumPy matmul's LHS and RHS must both be ndarrays. Scalars are not allowed.
match (&*unifier.get_ty(lhs), &*unifier.get_ty(rhs)) {
(
TypeEnum::TObj { obj_id: lhs_obj_id, .. },
TypeEnum::TObj { obj_id: rhs_obj_id, .. },
) if *lhs_obj_id == primitives.ndarray.obj_id(unifier).unwrap()
&& *rhs_obj_id == primitives.ndarray.obj_id(unifier).unwrap() =>
{
// LHS and RHS have valid types
}
_ => {
let lhs_str = unifier.stringify(lhs);
let rhs_str = unifier.stringify(rhs);
return Err(format!("ndarray.__matmul__ only accepts ndarray operands, but left operand has type {lhs_str}, and right operand has type {rhs_str}"));
}
}
let (_, lhs_ndims) = unpack_ndarray_var_tys(unifier, lhs);
let lhs_ndims = match &*unifier.get_ty_immutable(lhs_ndims) {
TypeEnum::TLiteral { values, .. } => {
@ -697,7 +678,6 @@ pub fn set_primitives_magic_methods(store: &PrimitiveStore, unifier: &mut Unifie
bool: bool_t,
uint32: uint32_t,
uint64: uint64_t,
str: str_t,
list: list_t,
ndarray: ndarray_t,
..
@ -743,9 +723,6 @@ pub fn set_primitives_magic_methods(store: &PrimitiveStore, unifier: &mut Unifie
impl_sign(unifier, store, bool_t, Some(int32_t));
impl_eq(unifier, store, bool_t, &[bool_t, ndarray_bool_t], None);
/* str ========= */
impl_cmpop(unifier, store, str_t, &[str_t], &[Cmpop::Eq, Cmpop::NotEq], Some(bool_t));
/* list ======== */
impl_binop(unifier, store, list_t, &[list_t], Some(list_t), &[Operator::Add]);
impl_binop(unifier, store, list_t, &[int32_t, int64_t], Some(list_t), &[Operator::Mult]);

View File

@ -183,10 +183,9 @@ impl<'a> Display for DisplayTypeError<'a> {
}
result
}
(
TypeEnum::TTuple { ty: ty1, is_vararg_ctx: is_vararg1 },
TypeEnum::TTuple { ty: ty2, is_vararg_ctx: is_vararg2 },
) if !is_vararg1 && !is_vararg2 && ty1.len() != ty2.len() => {
(TypeEnum::TTuple { ty: ty1 }, TypeEnum::TTuple { ty: ty2 })
if ty1.len() != ty2.len() =>
{
let t1 = self.unifier.stringify_with_notes(*t1, &mut notes);
let t2 = self.unifier.stringify_with_notes(*t2, &mut notes);
write!(f, "Tuple length mismatch: got {t1} and {t2}")

File diff suppressed because it is too large Load Diff

View File

@ -83,12 +83,7 @@ impl TestEnvironment {
});
with_fields(&mut unifier, int32, |unifier, fields| {
let add_ty = unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![FuncArg {
name: "other".into(),
ty: int32,
default_value: None,
is_vararg: false,
}],
args: vec![FuncArg { name: "other".into(), ty: int32, default_value: None }],
ret: int32,
vars: VarMap::new(),
}));
@ -229,12 +224,7 @@ impl TestEnvironment {
});
with_fields(&mut unifier, int32, |unifier, fields| {
let add_ty = unifier.add_ty(TypeEnum::TFunc(FunSignature {
args: vec![FuncArg {
name: "other".into(),
ty: int32,
default_value: None,
is_vararg: false,
}],
args: vec![FuncArg { name: "other".into(), ty: int32, default_value: None }],
ret: int32,
vars: VarMap::new(),
}));

View File

@ -1,4 +1,16 @@
use super::magic_methods::{Binop, HasOpInfo};
use indexmap::IndexMap;
use itertools::Itertools;
use std::cell::RefCell;
use std::collections::HashMap;
use std::fmt::{self, Display};
use std::iter::zip;
use std::rc::Rc;
use std::sync::{Arc, Mutex};
use std::{borrow::Cow, collections::HashSet};
use nac3parser::ast::{Cmpop, Location, StrRef, Unaryop};
use super::magic_methods::Binop;
use super::type_error::{TypeError, TypeErrorKind};
use super::unification_table::{UnificationKey, UnificationTable};
use crate::symbol_resolver::SymbolValue;
@ -6,16 +18,6 @@ use crate::toplevel::helper::PrimDef;
use crate::toplevel::{DefinitionId, TopLevelContext, TopLevelDef};
use crate::typecheck::magic_methods::OpInfo;
use crate::typecheck::type_inferencer::PrimitiveStore;
use indexmap::IndexMap;
use itertools::{repeat_n, Itertools};
use nac3parser::ast::{Cmpop, Location, StrRef, Unaryop};
use std::cell::RefCell;
use std::collections::HashMap;
use std::fmt::{self, Display};
use std::iter::{repeat, zip};
use std::rc::Rc;
use std::sync::{Arc, Mutex};
use std::{borrow::Cow, collections::HashSet};
#[cfg(test)]
mod test;
@ -113,7 +115,6 @@ pub struct FuncArg {
pub name: StrRef,
pub ty: Type,
pub default_value: Option<SymbolValue>,
pub is_vararg: bool,
}
impl FuncArg {
@ -232,12 +233,6 @@ pub enum TypeEnum {
TTuple {
/// The types of elements present in this tuple.
ty: Vec<Type>,
/// Whether this tuple is used in a vararg context.
///
/// If `true`, `ty` must only contain one type, and the tuple is assumed to contain any
/// number of `ty`-typed values.
is_vararg_ctx: bool,
},
/// An object type.
@ -532,7 +527,7 @@ impl Unifier {
TypeEnum::TVirtual { ty } => self.get_instantiations(*ty).map(|ty| {
ty.iter().map(|&ty| self.add_ty(TypeEnum::TVirtual { ty })).collect_vec()
}),
TypeEnum::TTuple { ty, is_vararg_ctx } => {
TypeEnum::TTuple { ty } => {
let tuples = ty
.iter()
.map(|ty| self.get_instantiations(*ty).unwrap_or_else(|| vec![*ty]))
@ -542,12 +537,7 @@ impl Unifier {
None
} else {
Some(
tuples
.into_iter()
.map(|ty| {
self.add_ty(TypeEnum::TTuple { ty, is_vararg_ctx: *is_vararg_ctx })
})
.collect(),
tuples.into_iter().map(|ty| self.add_ty(TypeEnum::TTuple { ty })).collect(),
)
}
}
@ -591,7 +581,7 @@ impl Unifier {
TVar { .. } => allowed_typevars.iter().any(|b| self.unification_table.unioned(a, *b)),
TCall { .. } => false,
TVirtual { ty } => self.is_concrete(*ty, allowed_typevars),
TTuple { ty, .. } => ty.iter().all(|ty| self.is_concrete(*ty, allowed_typevars)),
TTuple { ty } => ty.iter().all(|ty| self.is_concrete(*ty, allowed_typevars)),
TObj { params: vars, .. } => {
vars.values().all(|ty| self.is_concrete(*ty, allowed_typevars))
}
@ -659,7 +649,6 @@ impl Unifier {
// Get details about the function signature/parameters.
let num_params = signature.args.len();
let is_vararg = signature.args.iter().any(|arg| arg.is_vararg);
// Force the type vars in `b` and `signature' to be up-to-date.
let b = self.instantiate_fun(b, signature);
@ -748,7 +737,7 @@ impl Unifier {
};
// Check for "too many arguments"
if !is_vararg && num_params < posargs.len() {
if num_params < posargs.len() {
let expected_min_count =
signature.args.iter().filter(|param| param.is_required()).count();
let expected_max_count = num_params;
@ -781,19 +770,6 @@ impl Unifier {
type_check_arg(param.name, param.ty, arg_ty)?;
}
if is_vararg {
debug_assert!(!signature.args.is_empty());
let vararg_args = posargs.iter().skip(signature.args.len());
let vararg_param = signature.args.last().unwrap();
for (&arg_ty, param) in zip(vararg_args, repeat(vararg_param)) {
// `param_info` for this argument would've already been marked as supplied
// during non-vararg posarg typecheck
type_check_arg(param.name, param.ty, arg_ty)?;
}
}
// Now consume all keyword arguments and typecheck them.
for (&param_name, &arg_ty) in kwargs {
// We will also use this opportunity to check if this keyword argument is "legal".
@ -983,10 +959,7 @@ impl Unifier {
self.unify_impl(x, b, false)?;
self.set_a_to_b(a, x);
}
(
TVar { fields: Some(fields), range, is_const_generic: false, .. },
TTuple { ty, .. },
) => {
(TVar { fields: Some(fields), range, is_const_generic: false, .. }, TTuple { ty }) => {
let len = i32::try_from(ty.len()).unwrap();
for (k, v) in fields {
match *k {
@ -1007,18 +980,8 @@ impl Unifier {
self.unify_impl(v.ty, ty[ind as usize], false)
.map_err(|e| e.at(v.loc))?;
}
RecordKey::Str(s) => {
let tuple_fns = [
Cmpop::Eq.op_info().method_name,
Cmpop::NotEq.op_info().method_name,
];
if !tuple_fns.into_iter().any(|op| s.to_string() == op) {
return Err(TypeError::new(
TypeErrorKind::NoSuchField(*k, b),
v.loc,
));
}
RecordKey::Str(_) => {
return Err(TypeError::new(TypeErrorKind::NoSuchField(*k, b), v.loc))
}
}
}
@ -1093,47 +1056,15 @@ impl Unifier {
self.set_a_to_b(a, b);
}
(
TTuple { ty: ty1, is_vararg_ctx: is_vararg1 },
TTuple { ty: ty2, is_vararg_ctx: is_vararg2 },
) => {
// Rules for Tuples:
// - ty1: is_vararg && ty2: is_vararg -> ty1[0] == ty2[0]
// - ty1: is_vararg && ty2: !is_vararg -> type error (not enough info to infer the correct number of arguments)
// - ty1: !is_vararg && ty2: is_vararg -> ty1[..] == ty2[0]
// - ty1: !is_vararg && ty2: !is_vararg -> ty1.len() == ty2.len() && ty1[i] == ty2[i]
debug_assert!(!is_vararg1 || ty1.len() == 1);
debug_assert!(!is_vararg2 || ty2.len() == 1);
match (*is_vararg1, *is_vararg2) {
(true, true) => {
if self.unify_impl(ty1[0], ty2[0], false).is_err() {
return Self::incompatible_types(a, b);
}
}
(true, false) => return Self::incompatible_types(a, b),
(false, true) => {
for y in ty2 {
if self.unify_impl(ty1[0], *y, false).is_err() {
return Self::incompatible_types(a, b);
}
}
}
(false, false) => {
if ty1.len() != ty2.len() {
return Self::incompatible_types(a, b);
}
for (x, y) in ty1.iter().zip(ty2.iter()) {
if self.unify_impl(*x, *y, false).is_err() {
return Self::incompatible_types(a, b);
}
}
(TTuple { ty: ty1 }, TTuple { ty: ty2 }) => {
if ty1.len() != ty2.len() {
return Err(TypeError::new(TypeErrorKind::IncompatibleTypes(a, b), None));
}
for (x, y) in ty1.iter().zip(ty2.iter()) {
if self.unify_impl(*x, *y, false).is_err() {
return Err(TypeError::new(TypeErrorKind::IncompatibleTypes(a, b), None));
}
}
self.set_a_to_b(a, b);
}
(TVar { fields: Some(map), range, .. }, TObj { obj_id, fields, params }) => {
@ -1376,22 +1307,10 @@ impl Unifier {
TypeEnum::TLiteral { values, .. } => {
format!("const({})", values.iter().map(|v| format!("{v:?}")).join(", "))
}
TypeEnum::TTuple { ty, is_vararg_ctx } => {
if *is_vararg_ctx {
debug_assert_eq!(ty.len(), 1);
let field = self.internal_stringify(
*ty.iter().next().unwrap(),
obj_to_name,
var_to_name,
notes,
);
format!("tuple[*{field}]")
} else {
let mut fields = ty
.iter()
.map(|v| self.internal_stringify(*v, obj_to_name, var_to_name, notes));
format!("tuple[{}]", fields.join(", "))
}
TypeEnum::TTuple { ty } => {
let mut fields =
ty.iter().map(|v| self.internal_stringify(*v, obj_to_name, var_to_name, notes));
format!("tuple[{}]", fields.join(", "))
}
TypeEnum::TVirtual { ty } => {
format!(
@ -1416,21 +1335,17 @@ impl Unifier {
.args
.iter()
.map(|arg| {
let vararg_prefix = if arg.is_vararg { "*" } else { "" };
if let Some(dv) = &arg.default_value {
format!(
"{}:{}{}={}",
"{}:{}={}",
arg.name,
vararg_prefix,
self.internal_stringify(arg.ty, obj_to_name, var_to_name, notes),
dv
)
} else {
format!(
"{}:{}{}",
"{}:{}",
arg.name,
vararg_prefix,
self.internal_stringify(arg.ty, obj_to_name, var_to_name, notes)
)
}
@ -1516,7 +1431,7 @@ impl Unifier {
match &*ty {
TypeEnum::TRigidVar { .. } | TypeEnum::TLiteral { .. } => None,
TypeEnum::TVar { id, .. } => mapping.get(id).copied(),
TypeEnum::TTuple { ty, is_vararg_ctx } => {
TypeEnum::TTuple { ty } => {
let mut new_ty = Cow::from(ty);
for (i, t) in ty.iter().enumerate() {
if let Some(t1) = self.subst_impl(*t, mapping, cache) {
@ -1524,10 +1439,7 @@ impl Unifier {
}
}
if matches!(new_ty, Cow::Owned(_)) {
Some(self.add_ty(TypeEnum::TTuple {
ty: new_ty.into_owned(),
is_vararg_ctx: *is_vararg_ctx,
}))
Some(self.add_ty(TypeEnum::TTuple { ty: new_ty.into_owned() }))
} else {
None
}
@ -1687,37 +1599,16 @@ impl Unifier {
}
}
(TVar { range, .. }, _) => self.check_var_compatibility(b, range).or(Err(())),
(
TTuple { ty: ty1, is_vararg_ctx: is_vararg1 },
TTuple { ty: ty2, is_vararg_ctx: is_vararg2 },
) => {
if *is_vararg1 && *is_vararg2 {
let isect_ty = self.get_intersection(ty1[0], ty2[0])?;
Ok(isect_ty.map(|ty| self.add_ty(TTuple { ty: vec![ty], is_vararg_ctx: true })))
(TTuple { ty: ty1 }, TTuple { ty: ty2 }) if ty1.len() == ty2.len() => {
let ty: Vec<_> = zip(ty1.iter(), ty2.iter())
.map(|(a, b)| self.get_intersection(*a, *b))
.try_collect()?;
if ty.iter().any(Option::is_some) {
Ok(Some(self.add_ty(TTuple {
ty: zip(ty, ty1.iter()).map(|(a, b)| a.unwrap_or(*b)).collect(),
})))
} else {
let zip_iter: Box<dyn Iterator<Item = (&Type, &Type)>> =
match (*is_vararg1, *is_vararg2) {
(true, _) => Box::new(repeat_n(&ty1[0], ty2.len()).zip(ty2.iter())),
(_, false) => Box::new(ty1.iter().zip(repeat_n(&ty2[0], ty1.len()))),
_ => {
if ty1.len() != ty2.len() {
return Err(());
}
Box::new(ty1.iter().zip(ty2.iter()))
}
};
let ty: Vec<_> =
zip_iter.map(|(a, b)| self.get_intersection(*a, *b)).try_collect()?;
Ok(if ty.iter().any(Option::is_some) {
Some(self.add_ty(TTuple {
ty: zip(ty, ty1.iter()).map(|(a, b)| a.unwrap_or(*b)).collect(),
is_vararg_ctx: false,
}))
} else {
None
})
Ok(None)
}
}
// TODO(Derppening): #444

View File

@ -28,10 +28,7 @@ impl Unifier {
TypeEnum::TVar { fields: Some(map1), .. },
TypeEnum::TVar { fields: Some(map2), .. },
) => self.map_eq2(map1, map2),
(
TypeEnum::TTuple { ty: ty1, is_vararg_ctx: false },
TypeEnum::TTuple { ty: ty2, is_vararg_ctx: false },
) => {
(TypeEnum::TTuple { ty: ty1 }, TypeEnum::TTuple { ty: ty2 }) => {
ty1.len() == ty2.len()
&& ty1.iter().zip(ty2.iter()).all(|(t1, t2)| self.eq(*t1, *t2))
}
@ -181,7 +178,7 @@ impl TestEnvironment {
ty.push(result.0);
s = result.1;
}
(self.unifier.add_ty(TypeEnum::TTuple { ty, is_vararg_ctx: false }), &s[1..])
(self.unifier.add_ty(TypeEnum::TTuple { ty }), &s[1..])
}
"Record" => {
let mut s = &typ[end..];
@ -611,7 +608,7 @@ fn test_instantiation() {
let v1 = env.unifier.get_fresh_var_with_range(&[list_v, int], None, None).ty;
let v2 = env.unifier.get_fresh_var_with_range(&[list_int, float], None, None).ty;
let t = env.unifier.get_dummy_var().ty;
let tuple = env.unifier.add_ty(TypeEnum::TTuple { ty: vec![v, v1, v2], is_vararg_ctx: false });
let tuple = env.unifier.add_ty(TypeEnum::TTuple { ty: vec![v, v1, v2] });
let v3 = env.unifier.get_fresh_var_with_range(&[tuple, t], None, None).ty;
// t = TypeVar('t')
// v = TypeVar('v', int, bool)

View File

@ -238,7 +238,7 @@ impl<'a> EH_Frame<'a> {
/// From the [specification](https://refspecs.linuxfoundation.org/LSB_5.0.0/LSB-Core-generic/LSB-Core-generic/ehframechpt.html):
///
/// > Each CFI record contains a Common Information Entry (CIE) record followed by 1 or more Frame
/// > Description Entry (FDE) records.
/// Description Entry (FDE) records.
pub struct CFI_Record<'a> {
// It refers to the augmentation data that corresponds to 'R' in the augmentation string
fde_pointer_encoding: u8,

View File

@ -4,9 +4,6 @@ version = "0.1.0"
authors = ["M-Labs"]
edition = "2021"
[features]
no-escape-analysis = ["nac3core/no-escape-analysis"]
[dependencies]
parking_lot = "0.12"
nac3parser = { path = "../nac3parser" }

View File

@ -3,66 +3,23 @@
set -e
if [ -z "$1" ]; then
echo "No argument supplied"
exit 1
echo "Requires at least one argument"
exit 1
fi
declare -a nac3args
while [ $# -gt 1 ]; do
case "$1" in
--help)
echo "Usage: check_demo.sh [--debug] [-i686] -- [NAC3ARGS...] demo"
exit
;;
--debug)
debug=1
;;
-i686)
i686=1
;;
--)
shift
break
;;
*)
echo "Unrecognized argument \"$1\""
exit 1
;;
esac
shift
done
while [ $# -gt 1 ]; do
nac3args+=("$1")
shift
done
demo="$1"
echo "### Checking $demo..."
echo ">>>>>> Running $demo with the Python interpreter"
echo -n "Checking $demo... "
./interpret_demo.py "$demo" > interpreted.log
./run_demo.sh --out run.log "${nac3args[@]}" "$demo"
./run_demo.sh --lli --out run_lli.log "${nac3args[@]}" "$demo"
diff -Nau interpreted.log run.log
diff -Nau interpreted.log run_lli.log
echo "ok"
if [ -n "$i686" ]; then
echo "...... Trying NAC3's 32-bit code generator output"
if [ -n "$debug" ]; then
./run_demo.sh --debug -i686 --out run_32.log -- "${nac3args[@]}" "$demo"
else
./run_demo.sh -i686 --out run_32.log -- "${nac3args[@]}" "$demo"
fi
diff -Nau interpreted.log run_32.log
fi
echo "...... Trying NAC3's 64-bit code generator output"
if [ -n "$debug" ]; then
./run_demo.sh --debug --out run_64.log -- "${nac3args[@]}" "$demo"
else
./run_demo.sh --out run_64.log -- "${nac3args[@]}" "$demo"
fi
diff -Nau interpreted.log run_64.log
echo "...... OK"
rm -f interpreted.log \
run_32.log run_64.log
rm -f interpreted.log run.log run_lli.log

View File

@ -2,11 +2,6 @@
set -e
if [ "$1" == "--help" ]; then
echo "Usage: check_demos.sh [CHECKARGS...] [--] [NAC3ARGS...]"
exit
fi
count=0
for demo in src/*.py; do
./check_demo.sh "$@" "$demo"

View File

@ -6,12 +6,14 @@
#include <stdlib.h>
#include <string.h>
#define usize size_t
double dbl_nan(void) {
return NAN;
return NAN;
}
double dbl_inf(void) {
return INFINITY;
return INFINITY;
}
void output_bool(bool x) {
@ -19,19 +21,19 @@ void output_bool(bool x) {
}
void output_int32(int32_t x) {
printf("%" PRId32 "\n", x);
printf("%"PRId32"\n", x);
}
void output_int64(int64_t x) {
printf("%" PRId64 "\n", x);
printf("%"PRId64"\n", x);
}
void output_uint32(uint32_t x) {
printf("%" PRIu32 "\n", x);
printf("%"PRIu32"\n", x);
}
void output_uint64(uint64_t x) {
printf("%" PRIu64 "\n", x);
printf("%"PRIu64"\n", x);
}
void output_float64(double x) {
@ -52,7 +54,7 @@ void output_range(int32_t range[3]) {
}
void output_asciiart(int32_t x) {
static const char* chars = " .,-:;i+hHM$*#@ ";
static const char *chars = " .,-:;i+hHM$*#@ ";
if (x < 0) {
putchar('\n');
} else {
@ -61,15 +63,15 @@ void output_asciiart(int32_t x) {
}
struct cslice {
void* data;
size_t len;
void *data;
usize len;
};
void output_int32_list(struct cslice* slice) {
const int32_t* data = (int32_t*)slice->data;
void output_int32_list(struct cslice *slice) {
const int32_t *data = (int32_t *) slice->data;
putchar('[');
for (size_t i = 0; i < slice->len; ++i) {
for (usize i = 0; i < slice->len; ++i) {
if (i == slice->len - 1) {
printf("%d", data[i]);
} else {
@ -80,23 +82,23 @@ void output_int32_list(struct cslice* slice) {
putchar('\n');
}
void output_str(struct cslice* slice) {
const char* data = (const char*)slice->data;
void output_str(struct cslice *slice) {
const char *data = (const char *) slice->data;
for (size_t i = 0; i < slice->len; ++i) {
for (usize i = 0; i < slice->len; ++i) {
putchar(data[i]);
}
}
void output_strln(struct cslice* slice) {
void output_strln(struct cslice *slice) {
output_str(slice);
putchar('\n');
}
uint64_t dbg_stack_address(__attribute__((unused)) struct cslice* slice) {
uint64_t dbg_stack_address(__attribute__((unused)) struct cslice *slice) {
int i;
void* ptr = (void*)&i;
return (uintptr_t)ptr;
void *ptr = (void *) &i;
return (uintptr_t) ptr;
}
uint32_t __nac3_personality(uint32_t state, uint32_t exception_object, uint32_t context) {
@ -119,12 +121,11 @@ struct Exception {
uint32_t __nac3_raise(struct Exception* e) {
printf("__nac3_raise called. Exception details:\n");
printf(" ID: %" PRIu32 "\n", e->id);
printf(" Location: %*s:%" PRIu32 ":%" PRIu32 "\n", (int)e->file.len, (const char*)e->file.data, e->line,
e->column);
printf(" Function: %*s\n", (int)e->function.len, (const char*)e->function.data);
printf(" Message: \"%*s\"\n", (int)e->message.len, (const char*)e->message.data);
printf(" Params: {0}=%" PRId64 ", {1}=%" PRId64 ", {2}=%" PRId64 "\n", e->param[0], e->param[1], e->param[2]);
printf(" ID: %lld\n", e->id);
printf(" Location: %*s:%lld:%lld\n" , e->file.len, (const char*) e->file.data, e->line, e->column);
printf(" Function: %*s\n" , e->function.len, (const char*) e->function.data);
printf(" Message: \"%*s\"\n" , e->message.len, (const char*) e->message.data);
printf(" Params: {0}=%lld, {1}=%lld, {2}=%lld\n", e->param[0], e->param[1], e->param[2]);
exit(101);
__builtin_unreachable();
}

View File

@ -6,7 +6,6 @@ import importlib.machinery
import math
import numpy as np
import numpy.typing as npt
import scipy as sp
import pathlib
from numpy import int32, int64, uint32, uint64
@ -218,8 +217,6 @@ def patch(module):
module.np_ldexp = np.ldexp
module.np_hypot = np.hypot
module.np_nextafter = np.nextafter
module.np_transpose = np.transpose
module.np_reshape = np.reshape
# SciPy Math functions
module.sp_spec_erf = special.erf
@ -229,20 +226,6 @@ def patch(module):
module.sp_spec_j0 = special.j0
module.sp_spec_j1 = special.j1
# Linalg functions
module.np_dot = np.dot
module.np_linalg_cholesky = np.linalg.cholesky
module.np_linalg_qr = np.linalg.qr
module.np_linalg_svd = np.linalg.svd
module.np_linalg_inv = np.linalg.inv
module.np_linalg_pinv = np.linalg.pinv
module.np_linalg_matrix_power = np.linalg.matrix_power
module.np_linalg_det = np.linalg.det
module.sp_linalg_lu = lambda x: sp.linalg.lu(x, True)
module.sp_linalg_schur = sp.linalg.schur
module.sp_linalg_hessenberg = lambda x: sp.linalg.hessenberg(x, True)
def file_import(filename, prefix="file_import_"):
filename = pathlib.Path(filename)
modname = prefix + filename.stem

View File

View File

@ -1,114 +0,0 @@
# This file is automatically @generated by Cargo.
# It is not intended for manual editing.
version = 3
[[package]]
name = "approx"
version = "0.5.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "cab112f0a86d568ea0e627cc1d6be74a1e9cd55214684db5561995f6dad897c6"
dependencies = [
"num-traits",
]
[[package]]
name = "autocfg"
version = "1.3.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "0c4b4d0bd25bd0b74681c0ad21497610ce1b7c91b1022cd21c80c6fbdd9476b0"
[[package]]
name = "cslice"
version = "0.3.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "0f8cb7306107e4b10e64994de6d3274bd08996a7c1322a27b86482392f96be0a"
[[package]]
name = "libm"
version = "0.2.8"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "4ec2a862134d2a7d32d7983ddcdd1c4923530833c9f2ea1a44fc5fa473989058"
[[package]]
name = "linalg"
version = "0.1.0"
dependencies = [
"cslice",
"nalgebra",
]
[[package]]
name = "nalgebra"
version = "0.32.6"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "7b5c17de023a86f59ed79891b2e5d5a94c705dbe904a5b5c9c952ea6221b03e4"
dependencies = [
"approx",
"num-complex",
"num-rational",
"num-traits",
"simba",
"typenum",
]
[[package]]
name = "num-complex"
version = "0.4.6"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "73f88a1307638156682bada9d7604135552957b7818057dcef22705b4d509495"
dependencies = [
"num-traits",
]
[[package]]
name = "num-integer"
version = "0.1.46"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "7969661fd2958a5cb096e56c8e1ad0444ac2bbcd0061bd28660485a44879858f"
dependencies = [
"num-traits",
]
[[package]]
name = "num-rational"
version = "0.4.2"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "f83d14da390562dca69fc84082e73e548e1ad308d24accdedd2720017cb37824"
dependencies = [
"num-integer",
"num-traits",
]
[[package]]
name = "num-traits"
version = "0.2.19"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "071dfc062690e90b734c0b2273ce72ad0ffa95f0c74596bc250dcfd960262841"
dependencies = [
"autocfg",
"libm",
]
[[package]]
name = "paste"
version = "1.0.15"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "57c0d7b74b563b49d38dae00a0c37d4d6de9b432382b2892f0574ddcae73fd0a"
[[package]]
name = "simba"
version = "0.8.1"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "061507c94fc6ab4ba1c9a0305018408e312e17c041eb63bef8aa726fa33aceae"
dependencies = [
"approx",
"num-complex",
"num-traits",
"paste",
]
[[package]]
name = "typenum"
version = "1.17.0"
source = "registry+https://github.com/rust-lang/crates.io-index"
checksum = "42ff0bf0c66b8238c6f3b578df37d0b7848e55df8577b3f74f92a69acceeb825"

View File

@ -1,13 +0,0 @@
[package]
name = "linalg"
version = "0.1.0"
edition = "2021"
[lib]
crate-type = ["staticlib"]
[dependencies]
nalgebra = {version = "0.32.6", default-features = false, features = ["libm", "alloc"]}
cslice = "0.3.0"
[workspace]

View File

@ -1,406 +0,0 @@
// Uses `nalgebra` crate to invoke `np_linalg` and `sp_linalg` functions
// When converting between `nalgebra::Matrix` and `NDArray` following considerations are necessary
//
// * Both `nalgebra::Matrix` and `NDArray` require their content to be stored in row-major order
// * `NDArray` data pointer can be directly read and converted to `nalgebra::Matrix` (row and column number must be known)
// * `nalgebra::Matrix::as_slice` returns the content of matrix in column-major order and initial data needs to be transposed before storing it in `NDArray` data pointer
use core::slice;
use nalgebra::DMatrix;
fn report_error(
error_name: &str,
fn_name: &str,
file_name: &str,
line_num: u32,
col_num: u32,
err_msg: &str,
) -> ! {
panic!(
"Exception {} from {} in {}:{}:{}, message: {}",
error_name, fn_name, file_name, line_num, col_num, err_msg
);
}
pub struct InputMatrix {
pub ndims: usize,
pub dims: *const usize,
pub data: *mut f64,
}
impl InputMatrix {
fn get_dims(&mut self) -> Vec<usize> {
let dims = unsafe { slice::from_raw_parts(self.dims, self.ndims) };
dims.to_vec()
}
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_cholesky(mat1: *mut InputMatrix, out: *mut InputMatrix) {
let mat1 = mat1.as_mut().unwrap();
let out = out.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
report_error("ValueError", "np_linalg_cholesky", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
if dim1[0] != dim1[1] {
let err_msg =
format!("last 2 dimensions of the array must be square: {0} != {1}", dim1[0], dim1[1]);
report_error("LinAlgError", "np_linalg_cholesky", file!(), line!(), column!(), &err_msg);
}
let outdim = out.get_dims();
let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let matrix1 = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let result = matrix1.cholesky();
match result {
Some(res) => {
out_slice.copy_from_slice(res.unpack().transpose().as_slice());
}
None => {
report_error(
"LinAlgError",
"np_linalg_cholesky",
file!(),
line!(),
column!(),
"Matrix is not positive definite",
);
}
};
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_qr(
mat1: *mut InputMatrix,
out_q: *mut InputMatrix,
out_r: *mut InputMatrix,
) {
let mat1 = mat1.as_mut().unwrap();
let out_q = out_q.as_mut().unwrap();
let out_r = out_r.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
report_error("ValueError", "np_linalg_cholesky", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
let outq_dim = (*out_q).get_dims();
let outr_dim = (*out_r).get_dims();
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let out_q_slice = unsafe { slice::from_raw_parts_mut(out_q.data, outq_dim[0] * outq_dim[1]) };
let out_r_slice = unsafe { slice::from_raw_parts_mut(out_r.data, outr_dim[0] * outr_dim[1]) };
// Refer to https://github.com/dimforge/nalgebra/issues/735
let matrix1 = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let res = matrix1.qr();
let (q, r) = res.unpack();
// Uses different algo need to match numpy
out_q_slice.copy_from_slice(q.transpose().as_slice());
out_r_slice.copy_from_slice(r.transpose().as_slice());
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_svd(
mat1: *mut InputMatrix,
outu: *mut InputMatrix,
outs: *mut InputMatrix,
outvh: *mut InputMatrix,
) {
let mat1 = mat1.as_mut().unwrap();
let outu = outu.as_mut().unwrap();
let outs = outs.as_mut().unwrap();
let outvh = outvh.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
report_error("ValueError", "np_linalg_svd", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
let outu_dim = (*outu).get_dims();
let outs_dim = (*outs).get_dims();
let outvh_dim = (*outvh).get_dims();
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let out_u_slice = unsafe { slice::from_raw_parts_mut(outu.data, outu_dim[0] * outu_dim[1]) };
let out_s_slice = unsafe { slice::from_raw_parts_mut(outs.data, outs_dim[0]) };
let out_vh_slice =
unsafe { slice::from_raw_parts_mut(outvh.data, outvh_dim[0] * outvh_dim[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let result = matrix.svd(true, true);
out_u_slice.copy_from_slice(result.u.unwrap().transpose().as_slice());
out_s_slice.copy_from_slice(result.singular_values.as_slice());
out_vh_slice.copy_from_slice(result.v_t.unwrap().transpose().as_slice());
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_inv(mat1: *mut InputMatrix, out: *mut InputMatrix) {
let mat1 = mat1.as_mut().unwrap();
let out = out.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
report_error("ValueError", "np_linalg_inv", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
if dim1[0] != dim1[1] {
let err_msg =
format!("last 2 dimensions of the array must be square: {0} != {1}", dim1[0], dim1[1]);
report_error("LinAlgError", "np_linalg_inv", file!(), line!(), column!(), &err_msg);
}
let outdim = out.get_dims();
let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
if !matrix.is_invertible() {
report_error(
"LinAlgError",
"np_linalg_inv",
file!(),
line!(),
column!(),
"no inverse for Singular Matrix",
);
}
let inv = matrix.try_inverse().unwrap();
out_slice.copy_from_slice(inv.transpose().as_slice());
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_pinv(mat1: *mut InputMatrix, out: *mut InputMatrix) {
let mat1 = mat1.as_mut().unwrap();
let out = out.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
report_error("ValueError", "np_linalg_pinv", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
let outdim = out.get_dims();
let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let svd = matrix.svd(true, true);
let inv = svd.pseudo_inverse(1e-15);
match inv {
Ok(m) => {
out_slice.copy_from_slice(m.transpose().as_slice());
}
Err(err_msg) => {
report_error("LinAlgError", "np_linalg_pinv", file!(), line!(), column!(), err_msg);
}
}
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_matrix_power(
mat1: *mut InputMatrix,
mat2: *mut InputMatrix,
out: *mut InputMatrix,
) {
let mat1 = mat1.as_mut().unwrap();
let mat2 = mat2.as_mut().unwrap();
let out = out.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D", mat1.ndims);
report_error("ValueError", "np_linalg_matrix_power", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
let power = unsafe { slice::from_raw_parts_mut(mat2.data, 1) };
let power = power[0];
let outdim = out.get_dims();
let out_slice = unsafe { slice::from_raw_parts_mut(out.data, outdim[0] * outdim[1]) };
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let abs_pow = power.abs();
let matrix1 = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let mut result = matrix1.pow(abs_pow as u32);
if power < 0.0 {
if !result.is_invertible() {
report_error(
"LinAlgError",
"np_linalg_inv",
file!(),
line!(),
column!(),
"no inverse for Singular Matrix",
);
}
result = result.try_inverse().unwrap();
}
out_slice.copy_from_slice(result.transpose().as_slice());
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn np_linalg_det(mat1: *mut InputMatrix, out: *mut InputMatrix) {
let mat1 = mat1.as_mut().unwrap();
let out = out.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
report_error("ValueError", "np_linalg_det", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
let out_slice = unsafe { slice::from_raw_parts_mut(out.data, 1) };
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
if !matrix.is_square() {
let err_msg =
format!("last 2 dimensions of the array must be square: {0} != {1}", dim1[0], dim1[1]);
report_error("LinAlgError", "np_linalg_inv", file!(), line!(), column!(), &err_msg);
}
out_slice[0] = matrix.determinant();
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn sp_linalg_lu(
mat1: *mut InputMatrix,
out_l: *mut InputMatrix,
out_u: *mut InputMatrix,
) {
let mat1 = mat1.as_mut().unwrap();
let out_l = out_l.as_mut().unwrap();
let out_u = out_u.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
report_error("ValueError", "sp_linalg_lu", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
let outl_dim = (*out_l).get_dims();
let outu_dim = (*out_u).get_dims();
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let out_l_slice = unsafe { slice::from_raw_parts_mut(out_l.data, outl_dim[0] * outl_dim[1]) };
let out_u_slice = unsafe { slice::from_raw_parts_mut(out_u.data, outu_dim[0] * outu_dim[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let (_, l, u) = matrix.lu().unpack();
out_l_slice.copy_from_slice(l.transpose().as_slice());
out_u_slice.copy_from_slice(u.transpose().as_slice());
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn sp_linalg_schur(
mat1: *mut InputMatrix,
out_t: *mut InputMatrix,
out_z: *mut InputMatrix,
) {
let mat1 = mat1.as_mut().unwrap();
let out_t = out_t.as_mut().unwrap();
let out_z = out_z.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
report_error("ValueError", "sp_linalg_schur", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
if dim1[0] != dim1[1] {
let err_msg =
format!("last 2 dimensions of the array must be square: {0} != {1}", dim1[0], dim1[1]);
report_error("LinAlgError", "np_linalg_schur", file!(), line!(), column!(), &err_msg);
}
let out_t_dim = (*out_t).get_dims();
let out_z_dim = (*out_z).get_dims();
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let out_t_slice = unsafe { slice::from_raw_parts_mut(out_t.data, out_t_dim[0] * out_t_dim[1]) };
let out_z_slice = unsafe { slice::from_raw_parts_mut(out_z.data, out_z_dim[0] * out_z_dim[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let (z, t) = matrix.schur().unpack();
out_t_slice.copy_from_slice(t.transpose().as_slice());
out_z_slice.copy_from_slice(z.transpose().as_slice());
}
/// # Safety
///
/// `mat1` should point to a valid 2DArray of `f64` floats in row-major order
#[no_mangle]
pub unsafe extern "C" fn sp_linalg_hessenberg(
mat1: *mut InputMatrix,
out_h: *mut InputMatrix,
out_q: *mut InputMatrix,
) {
let mat1 = mat1.as_mut().unwrap();
let out_h = out_h.as_mut().unwrap();
let out_q = out_q.as_mut().unwrap();
if mat1.ndims != 2 {
let err_msg = format!("expected 2D Vector Input, but received {}D input", mat1.ndims);
report_error("ValueError", "sp_linalg_hessenberg", file!(), line!(), column!(), &err_msg);
}
let dim1 = (*mat1).get_dims();
if dim1[0] != dim1[1] {
let err_msg =
format!("last 2 dimensions of the array must be square: {} != {}", dim1[0], dim1[1]);
report_error("LinAlgError", "sp_linalg_hessenberg", file!(), line!(), column!(), &err_msg);
}
let out_h_dim = (*out_h).get_dims();
let out_q_dim = (*out_q).get_dims();
let data_slice1 = unsafe { slice::from_raw_parts_mut(mat1.data, dim1[0] * dim1[1]) };
let out_h_slice = unsafe { slice::from_raw_parts_mut(out_h.data, out_h_dim[0] * out_h_dim[1]) };
let out_q_slice = unsafe { slice::from_raw_parts_mut(out_q.data, out_q_dim[0] * out_q_dim[1]) };
let matrix = DMatrix::from_row_slice(dim1[0], dim1[1], data_slice1);
let (q, h) = matrix.hessenberg().unpack();
out_h_slice.copy_from_slice(h.transpose().as_slice());
out_q_slice.copy_from_slice(q.transpose().as_slice());
}

View File

@ -2,9 +2,6 @@
set -e
: "${DEMO_LINALG_STUB:=linalg/target/release/liblinalg.a}"
: "${DEMO_LINALG_STUB32:=linalg/target/i686-unknown-linux-gnu/release/liblinalg.a}"
if [ -z "$1" ]; then
echo "No argument supplied"
exit 1
@ -14,26 +11,25 @@ declare -a nac3args
while [ $# -ge 1 ]; do
case "$1" in
--help)
echo "Usage: run_demo.sh [--help] [--out OUTFILE] [--debug] [-i686] -- [NAC3ARGS...] demo"
echo "Usage: run_demo.sh [--help] [--out OUTFILE] [--lli] [--debug] -- [NAC3ARGS...]"
exit
;;
--out)
shift
outfile="$1"
;;
--lli)
use_lli=1
;;
--debug)
debug=1
;;
-i686)
i686=1
;;
--)
shift
break
;;
*)
echo "Unrecognized argument \"$1\""
exit 1
break
;;
esac
shift
@ -54,19 +50,29 @@ else
fi
rm -f ./*.o ./*.bc demo
if [ -z "$i686" ]; then
if [ -z "$use_lli" ]; then
$nac3standalone "${nac3args[@]}"
clang -c -std=gnu11 -Wall -Wextra -O3 -o demo.o demo.c
clang -o demo module.o demo.o $DEMO_LINALG_STUB -lm -Wl,--no-warn-search-mismatch
else
$nac3standalone --triple i686-unknown-linux-gnu --target-features +sse2 "${nac3args[@]}"
clang -m32 -c -std=gnu11 -Wall -Wextra -O3 -msse2 -o demo.o demo.c
clang -m32 -o demo module.o demo.o $DEMO_LINALG_STUB32 -lm -Wl,--no-warn-search-mismatch
fi
if [ -z "$outfile" ]; then
./demo
clang -c -std=gnu11 -Wall -Wextra -O3 -o demo.o demo.c
clang -lm -o demo module.o demo.o
if [ -z "$outfile" ]; then
./demo
else
./demo > "$outfile"
fi
else
./demo > "$outfile"
$nac3standalone --emit-llvm "${nac3args[@]}"
clang -c -std=gnu11 -Wall -Wextra -O3 -emit-llvm -o demo.bc demo.c
shopt -s nullglob
llvm-link -o nac3out.bc module*.bc main.bc
shopt -u nullglob
if [ -z "$outfile" ]; then
lli --extra-module demo.bc --extra-module irrt.bc nac3out.bc
else
lli --extra-module demo.bc --extra-module irrt.bc nac3out.bc > "$outfile"
fi
fi

View File

@ -1,76 +0,0 @@
@extern
def output_int32(x: int32):
...
@extern
def output_bool(x: bool):
...
def example1():
x, *ys, z = (1, 2, 3, 4, 5)
output_int32(x)
output_int32(len(ys))
output_int32(ys[0])
output_int32(ys[1])
output_int32(ys[2])
output_int32(z)
def example2():
x, y, *zs = (1, 2, 3, 4, 5)
output_int32(x)
output_int32(y)
output_int32(len(zs))
output_int32(zs[0])
output_int32(zs[1])
output_int32(zs[2])
def example3():
*xs, y, z = (1, 2, 3, 4, 5)
output_int32(len(xs))
output_int32(xs[0])
output_int32(xs[1])
output_int32(xs[2])
output_int32(y)
output_int32(z)
def example4():
*xs, y, z = (4, 5)
output_int32(len(xs))
output_int32(y)
output_int32(z)
def example5():
# Example from: https://docs.python.org/3/reference/simple_stmts.html#assignment-statements
x = [0, 1]
i = 0
i, x[i] = 1, 2 # i is updated, then x[i] is updated
output_int32(i)
output_int32(x[0])
output_int32(x[1])
class A:
value: int32
def __init__(self):
self.value = 1000
def example6():
ws = [88, 7, 8]
a = A()
x, [y, *ys, a.value], ws[0], (ws[0],) = 1, (2, False, 4, 5), 99, (6,)
output_int32(x)
output_int32(y)
output_bool(ys[0])
output_int32(ys[1])
output_int32(a.value)
output_int32(ws[0])
output_int32(ws[1])
output_int32(ws[2])
def run() -> int32:
example1()
example2()
example3()
example4()
example5()
example6()
return 0

View File

@ -4,64 +4,51 @@ from __future__ import annotations
def output_int32(x: int32):
...
class A:
a: int32
def __init__(self, a: int32):
self.a = a
def output_all_fields(self):
output_int32(self.a)
def set_a(self, a: int32):
self.a = a
class B(A):
b: int32
def __init__(self, b: int32):
A.__init__(self, b + 1)
self.set_b(b)
def output_parent_fields(self):
A.output_all_fields(self)
def output_all_fields(self):
A.output_all_fields(self)
output_int32(self.b)
def set_b(self, b: int32):
self.b = b
class C(B):
class C:
c: int32
a: int32
b: int32
def __init__(self):
self.a = 42
self.b = 33
self.c = 12
def __init__(self, c: int32):
B.__init__(self, c + 1)
self.c = c
def output_parent_fields(self):
B.output_all_fields(self)
def output_all_fields(self):
B.output_all_fields(self)
def test2(self):
output_int32(999)
output_int32(self.a)
output_int32(self.b)
output_int32(self.c)
self.a = 23
class D(C):
def __init__(self):
# C.__init__(self)
self.test()
self.b = 1
self.c = 2
C.test2(self)
#self.a()
# self.test()
# C.test2(self)
# self.a = 2
# __main__.C.__init__(self)
def set_c(self, c: int32):
self.c = c
def test(self):
self.a = 2
def run() -> int32:
ccc = C(10)
ccc.output_all_fields()
ccc.set_a(1)
ccc.set_b(2)
ccc.set_c(3)
ccc.output_all_fields()
x = D()
output_int32(x.a)
output_int32(x.b)
output_int32(x.c)
bbb = B(10)
bbb.set_a(9)
bbb.set_b(8)
bbb.output_all_fields()
ccc.output_all_fields()
# aaa = A(5)
# bbb = B(2)
# aaa.f1()
# bbb.f1()
return 0

View File

@ -1429,142 +1429,6 @@ def test_ndarray_nextafter_broadcast_rhs_scalar():
output_ndarray_float_2(nextafter_x_zeros)
output_ndarray_float_2(nextafter_x_ones)
def test_ndarray_transpose():
x: ndarray[float, 2] = np_array([[1., 2., 3.], [4., 5., 6.]])
y = np_transpose(x)
z = np_transpose(y)
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_reshape():
w: ndarray[float, 1] = np_array([1., 2., 3., 4., 5., 6., 7., 8., 9., 10.])
x = np_reshape(w, (1, 2, 1, -1))
y = np_reshape(x, [2, -1])
z = np_reshape(y, 10)
x1: ndarray[int32, 1] = np_array([1, 2, 3, 4])
x2: ndarray[int32, 2] = np_reshape(x1, (2, 2))
output_ndarray_float_1(w)
output_ndarray_float_2(y)
output_ndarray_float_1(z)
def test_ndarray_dot():
x1: ndarray[float, 1] = np_array([5.0, 1.0, 4.0, 2.0])
y1: ndarray[float, 1] = np_array([5.0, 1.0, 6.0, 6.0])
z1 = np_dot(x1, y1)
x2: ndarray[int32, 1] = np_array([5, 1, 4, 2])
y2: ndarray[int32, 1] = np_array([5, 1, 6, 6])
z2 = np_dot(x2, y2)
x3: ndarray[bool, 1] = np_array([True, True, True, True])
y3: ndarray[bool, 1] = np_array([True, True, True, True])
z3 = np_dot(x3, y3)
z4 = np_dot(2, 3)
z5 = np_dot(2., 3.)
z6 = np_dot(True, False)
output_float64(z1)
output_int32(z2)
output_bool(z3)
output_int32(z4)
output_float64(z5)
output_bool(z6)
def test_ndarray_cholesky():
x: ndarray[float, 2] = np_array([[5.0, 1.0], [1.0, 4.0]])
y = np_linalg_cholesky(x)
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_qr():
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 8.0, -8.5]])
y, z = np_linalg_qr(x)
output_ndarray_float_2(x)
# QR Factorization is not unique and gives different results in numpy and nalgebra
# Reverting the decomposition to compare the initial arrays
a = y @ z
output_ndarray_float_2(a)
def test_ndarray_linalg_inv():
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 8.0, -8.5]])
y = np_linalg_inv(x)
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_pinv():
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5]])
y = np_linalg_pinv(x)
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_matrix_power():
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 8.0, -8.5]])
y = np_linalg_matrix_power(x, -9)
output_ndarray_float_2(x)
output_ndarray_float_2(y)
def test_ndarray_det():
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 8.0, -8.5]])
y = np_linalg_det(x)
output_ndarray_float_2(x)
output_float64(y)
def test_ndarray_schur():
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 8.0, -8.5]])
t, z = sp_linalg_schur(x)
output_ndarray_float_2(x)
# Schur Factorization is not unique and gives different results in scipy and nalgebra
# Reverting the decomposition to compare the initial arrays
a = (z @ t) @ np_linalg_inv(z)
output_ndarray_float_2(a)
def test_ndarray_hessenberg():
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 5.0, 8.5]])
h, q = sp_linalg_hessenberg(x)
output_ndarray_float_2(x)
# Hessenberg Factorization is not unique and gives different results in scipy and nalgebra
# Reverting the decomposition to compare the initial arrays
a = (q @ h) @ np_linalg_inv(q)
output_ndarray_float_2(a)
def test_ndarray_lu():
x: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5]])
l, u = sp_linalg_lu(x)
output_ndarray_float_2(x)
output_ndarray_float_2(l)
output_ndarray_float_2(u)
def test_ndarray_svd():
w: ndarray[float, 2] = np_array([[-5.0, -1.0, 2.0], [-1.0, 4.0, 7.5], [-1.0, 8.0, -8.5]])
x, y, z = np_linalg_svd(w)
output_ndarray_float_2(w)
# SVD Factorization is not unique and gives different results in numpy and nalgebra
# Reverting the decomposition to compare the initial arrays
a = x @ z
output_ndarray_float_2(a)
output_ndarray_float_1(y)
def run() -> int32:
test_ndarray_ctor()
test_ndarray_empty()
@ -1669,7 +1533,6 @@ def run() -> int32:
test_ndarray_round()
test_ndarray_floor()
test_ndarray_ceil()
test_ndarray_min()
test_ndarray_minimum()
test_ndarray_minimum_broadcast()
@ -1744,18 +1607,5 @@ def run() -> int32:
test_ndarray_nextafter_broadcast()
test_ndarray_nextafter_broadcast_lhs_scalar()
test_ndarray_nextafter_broadcast_rhs_scalar()
test_ndarray_transpose()
test_ndarray_reshape()
test_ndarray_dot()
test_ndarray_cholesky()
test_ndarray_qr()
test_ndarray_svd()
test_ndarray_linalg_inv()
test_ndarray_pinv()
test_ndarray_matrix_power()
test_ndarray_det()
test_ndarray_lu()
test_ndarray_schur()
test_ndarray_hessenberg()
return 0

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@ -1,30 +0,0 @@
@extern
def output_bool(x: bool):
...
def str_eq():
output_bool("" == "")
output_bool("a" == "")
output_bool("a" == "b")
output_bool("b" == "a")
output_bool("a" == "a")
output_bool("test string" == "test string")
output_bool("test string1" == "test string2")
def str_ne():
output_bool("" != "")
output_bool("a" != "")
output_bool("a" != "b")
output_bool("b" != "a")
output_bool("a" != "a")
output_bool("test string" != "test string")
output_bool("test string1" != "test string2")
def run() -> int32:
str_eq()
str_ne()
return 0

View File

@ -1,7 +1,3 @@
@extern
def output_bool(b: bool):
...
@extern
def output_int32_list(x: list[int32]):
...
@ -17,41 +13,6 @@ class A:
self.a = a
self.b = b
def test_tuple_eq():
# 0-len
output_bool(() == ())
# 1-len
output_bool((1,) == ())
output_bool(() == (1,))
output_bool((1,) == (1,))
output_bool((1,) == (2,))
# # 2-len
output_bool((1, 2) == ())
output_bool(() == (1, 2))
output_bool((1,) == (1, 2))
output_bool((1, 2) == (1,))
output_bool((2, 2) == (1, 2))
output_bool((1, 2) == (2, 2))
def test_tuple_ne():
# 0-len
output_bool(() != ())
# 1-len
output_bool((1,) != ())
output_bool(() != (1,))
output_bool((1,) != (1,))
output_bool((1,) != (2,))
# 2-len
output_bool((1, 2) != ())
output_bool(() != (1, 2))
output_bool((1,) != (1, 2))
output_bool((1, 2) != (1,))
output_bool((2, 2) != (1, 2))
output_bool((1, 2) != (2, 2))
def run() -> int32:
data = [0, 1, 2, 3]
@ -64,15 +25,5 @@ def run() -> int32:
output_int32(tl[0][0])
output_int32(tl[0][1])
output_int32(tl[1])
output_int32(len(()))
output_int32(len((1,)))
output_int32(len((1, 2)))
output_int32(len((1, 2, 3)))
output_int32(len((1, 2, 3, 4)))
output_int32(len((1, 2, 3, 4, 5)))
test_tuple_eq()
test_tuple_ne()
return 0

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@ -1,11 +0,0 @@
def f(*args: int32):
pass
def run() -> int32:
f()
f(1)
f(1, 2)
f(1, 2, 3)
return 0

View File

@ -15,6 +15,7 @@ use std::{collections::HashMap, sync::Arc};
pub struct ResolverInternal {
pub id_to_type: Mutex<HashMap<StrRef, Type>>,
pub id_to_def: Mutex<HashMap<StrRef, DefinitionId>>,
pub class_names: Mutex<HashMap<StrRef, Type>>,
pub module_globals: Mutex<HashMap<StrRef, SymbolValue>>,
pub str_store: Mutex<HashMap<String, i32>>,
}
@ -58,7 +59,7 @@ impl SymbolResolver for Resolver {
_: StrRef,
_: &mut CodeGenContext<'ctx, '_>,
) -> Option<ValueEnum<'ctx>> {
unimplemented!()
None
}
fn get_identifier_def(&self, id: StrRef) -> Result<DefinitionId, HashSet<String>> {

View File

@ -9,11 +9,15 @@
#![allow(clippy::too_many_lines, clippy::wildcard_imports)]
use clap::Parser;
use inkwell::context::Context;
use inkwell::{
memory_buffer::MemoryBuffer, passes::PassBuilderOptions, support::is_multithreaded, targets::*,
OptimizationLevel,
};
use parking_lot::{Mutex, RwLock};
use std::collections::HashSet;
use std::num::NonZeroUsize;
use std::{collections::HashMap, fs, path::Path, sync::Arc};
use nac3core::{
codegen::{
concrete_type::ConcreteTypeStore, irrt::load_irrt, CodeGenLLVMOptions,
@ -35,10 +39,6 @@ use nac3parser::{
ast::{Constant, Expr, ExprKind, StmtKind, StrRef},
parser,
};
use parking_lot::{Mutex, RwLock};
use std::collections::HashSet;
use std::num::NonZeroUsize;
use std::{collections::HashMap, fs, path::Path, sync::Arc};
mod basic_symbol_resolver;
use basic_symbol_resolver::*;
@ -241,6 +241,8 @@ fn handle_assignment_pattern(
}
fn main() {
const SIZE_T: u32 = usize::BITS;
let cli = CommandLineArgs::parse();
let CommandLineArgs { file_name, threads, opt_level, emit_llvm, triple, mcpu, target_features } =
cli;
@ -273,24 +275,6 @@ fn main() {
_ => OptimizationLevel::Aggressive,
};
let target_machine_options = CodeGenTargetMachineOptions {
triple,
cpu: mcpu,
features: target_features,
reloc_mode: RelocMode::PIC,
..host_target_machine
};
let size_t = Context::create()
.ptr_sized_int_type(
&target_machine_options
.create_target_machine(opt_level)
.map(|tm| tm.get_target_data())
.unwrap(),
None,
)
.get_bit_width();
let program = match fs::read_to_string(file_name.clone()) {
Ok(program) => program,
Err(err) => {
@ -299,13 +283,14 @@ fn main() {
}
};
let primitive: PrimitiveStore = TopLevelComposer::make_primitives(size_t).0;
let primitive: PrimitiveStore = TopLevelComposer::make_primitives(SIZE_T).0;
let (mut composer, builtins_def, builtins_ty) =
TopLevelComposer::new(vec![], vec![], ComposerConfig::default(), size_t);
TopLevelComposer::new(vec![], ComposerConfig::default(), SIZE_T);
let internal_resolver: Arc<ResolverInternal> = ResolverInternal {
id_to_type: builtins_ty.into(),
id_to_def: builtins_def.into(),
class_names: Mutex::default(),
module_globals: Mutex::default(),
str_store: Mutex::default(),
}
@ -313,15 +298,6 @@ fn main() {
let resolver =
Arc::new(Resolver(internal_resolver.clone())) as Arc<dyn SymbolResolver + Send + Sync>;
let context = inkwell::context::Context::create();
// Process IRRT
let irrt = load_irrt(&context, resolver.as_ref());
if emit_llvm {
irrt.write_bitcode_to_path(Path::new("irrt.bc"));
}
// Process the Python script
let parser_result = parser::parse_program(&program, file_name.into()).unwrap();
for stmt in parser_result {
@ -397,7 +373,16 @@ fn main() {
instance_to_stmt[""].clone()
};
let llvm_options = CodeGenLLVMOptions { opt_level, target: target_machine_options };
let llvm_options = CodeGenLLVMOptions {
opt_level,
target: CodeGenTargetMachineOptions {
triple,
cpu: mcpu,
features: target_features,
reloc_mode: RelocMode::PIC,
..host_target_machine
},
};
let task = CodeGenTask {
subst: Vec::default(),
@ -420,14 +405,14 @@ fn main() {
membuffer.lock().push(buffer);
})));
let threads = (0..threads)
.map(|i| Box::new(DefaultCodeGenerator::new(format!("module{i}"), size_t)))
.map(|i| Box::new(DefaultCodeGenerator::new(format!("module{i}"), SIZE_T)))
.collect();
let (registry, handles) = WorkerRegistry::create_workers(threads, top_level, &llvm_options, &f);
registry.add_task(task);
registry.wait_tasks_complete(handles);
// Link all modules together into `main`
let buffers = membuffers.lock();
let context = inkwell::context::Context::create();
let main = context
.create_module_from_ir(MemoryBuffer::create_from_memory_range(&buffers[0], "main"))
.unwrap();
@ -447,9 +432,12 @@ fn main() {
main.link_in_module(other).unwrap();
}
let irrt = load_irrt(&context);
if emit_llvm {
irrt.write_bitcode_to_path(Path::new("irrt.bc"));
}
main.link_in_module(irrt).unwrap();
// Private all functions except "run"
let mut function_iter = main.get_first_function();
while let Some(func) = function_iter {
if func.count_basic_blocks() > 0 && func.get_name().to_str().unwrap() != "run" {
@ -458,7 +446,6 @@ fn main() {
function_iter = func.get_next_function();
}
// Optimize `main`
let target_machine = llvm_options
.target
.create_target_machine(llvm_options.opt_level)
@ -472,7 +459,6 @@ fn main() {
panic!("Failed to run optimization for module `main`: {}", err.to_string());
}
// Write output
target_machine
.write_to_file(&main, FileType::Object, Path::new("module.o"))
.expect("couldn't write module to file");

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